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Highway-rail grade crossing (HRGC) accidents pose a serious risk of safety to highway users, including pedestrians trying to cross HRGCs. A significant increase in the number of HRGC accidents globally calls for greater research efforts, which are not limited to the analysis of accidents at HRGCs but also understanding user perception, driver behavior, potential conflicting areas at crossings, effectiveness of countermeasures and user perception towards them. HRGC safety is one of the priority areas in the State of Florida, since the state HRGCs experienced a total of 429 injuries and 146 fatalities between 2010 and 2019 with a significant increase in HRGC accidents over the last years. The present study aims to conduct a comprehensive analysis of the HRGCs that experienced accidents in Florida over the last years. The databases maintained by the Federal Rail Administration (FRA) are used to gather the relevant information for a total of 578 crossings that experienced at least one accident from 2010 to 2019. In contrast with many of the previous efforts, this study investigates a wide range of various factors, including physical and operational characteristics of crossings, vehicle and train characteristics, spatial characteristics, temporal and environmental characteristics, driver actions and related characteristics, and other relevant information. The outcomes of this research will help better understanding the major causes behind accidents at the HRGCs in the State of Florida in a holistic way by considering a variety of relevant factors, which will assist the appropriate stakeholders with implementation of safety improvement projects across the state.
Prashant Singh; Junayed Pasha; Amir Khorram-Manesh; Krzysztof Goniewicz; Abdolreza Roshani; Maxim Dulebenets. A Holistic Analysis of Train-Vehicle Accidents at Highway-Rail Grade Crossings in Florida. Sustainability 2021, 13, 8842 .
AMA StylePrashant Singh, Junayed Pasha, Amir Khorram-Manesh, Krzysztof Goniewicz, Abdolreza Roshani, Maxim Dulebenets. A Holistic Analysis of Train-Vehicle Accidents at Highway-Rail Grade Crossings in Florida. Sustainability. 2021; 13 (16):8842.
Chicago/Turabian StylePrashant Singh; Junayed Pasha; Amir Khorram-Manesh; Krzysztof Goniewicz; Abdolreza Roshani; Maxim Dulebenets. 2021. "A Holistic Analysis of Train-Vehicle Accidents at Highway-Rail Grade Crossings in Florida." Sustainability 13, no. 16: 8842.
Social distancing plays a critical role in reducing the disease diffusion risk during the COVID-19 pandemic and post-pandemic period. In order to explore the social distancing obedience behavior, a comprehensive survey was conducted in this study by collecting data from 1064 Chinese residents in January 2021 by means of a questionnaire. Structural equation modeling (SEM) and hierarchical linear regression (HLR) analyses were employed to investigate the research hypotheses considered, testing the three influencing factors of social distancing obedience behavior: public guidance, risk perception, and regulation punishment. The reliability and validity of the measurements are demonstrated. The outcomes from the conducted analyses show that the public guidance significantly affects risk perception of individuals, while risk perception imposes a positive impact on social distancing obedience behavior. Moreover, risk perception serves a mediating role in the relationship between the public guidance and social distancing obedience behavior. In addition, regulation punishment positively predicts social distancing obedience behavior and could even have a greater effect by enhancing risk perception. Hence, this study suggests that the relevant authorities and agencies implement strong social distancing policies during the COVID-19 post-pandemic period from the perspective of promoting the public guidance, risk perception, and regulation punishment.
Jinghan Yuan; Hansong Zou; Kefan Xie; Maxim Dulebenets. An Assessment of Social Distancing Obedience Behavior during the COVID-19 Post-Epidemic Period in China: A Cross-Sectional Survey. Sustainability 2021, 13, 8091 .
AMA StyleJinghan Yuan, Hansong Zou, Kefan Xie, Maxim Dulebenets. An Assessment of Social Distancing Obedience Behavior during the COVID-19 Post-Epidemic Period in China: A Cross-Sectional Survey. Sustainability. 2021; 13 (14):8091.
Chicago/Turabian StyleJinghan Yuan; Hansong Zou; Kefan Xie; Maxim Dulebenets. 2021. "An Assessment of Social Distancing Obedience Behavior during the COVID-19 Post-Epidemic Period in China: A Cross-Sectional Survey." Sustainability 13, no. 14: 8091.
Automation is expected to effectively address the growing demand for passenger and freight transportation, safety issues, human errors, and increasing congestion. The growth of autonomous vehicles using the state-of-the-art connected vehicle technologies has paved the way for the development of passenger and freight autonomous trains (ATs), also known as driverless trains. ATs are fully automated trains that are centrally controlled using advanced communication and internet technologies, such as high-speed internet (5G) technology, Internet of Things, dedicated short range communications, digital video detection cameras, and artificial intelligence-based methods. The current study focuses on a detailed up-to-date review of the existing trends, technologies, advancements, and challenges in the deployment of ATs with a full automation level in rail transportation. The basic AT features along with the key technologies that are instrumental for the AT deployment and operations are discussed in detail. Furthermore, a comprehensive evaluation of the state-of-the-art research efforts is performed as well with a specific emphasis on the issues associated with the AT deployment, user perception and outlook for ATs, innovative concepts and models that could be used for the AT design, and the AT operations at highway-rail grade crossings. Based on the conducted review, this study determines the main advantages and challenges from the AT deployment. The identified challenges have to be collaboratively addressed by the relevant stakeholders, including railroad companies, researchers, and government representatives, to facilitate the AT development and deployment considering the perspectives of future users and without affecting the safety level.
Prashant Singh; Maxim A. Dulebenets; Junayed Pasha; Ernesto D. R. Santibanez Gonzalez; Yui-Yip Lau; Raphael Kampmann. Deployment of Autonomous Trains in Rail Transportation: Current Trends and Existing Challenges. IEEE Access 2021, 9, 1 -1.
AMA StylePrashant Singh, Maxim A. Dulebenets, Junayed Pasha, Ernesto D. R. Santibanez Gonzalez, Yui-Yip Lau, Raphael Kampmann. Deployment of Autonomous Trains in Rail Transportation: Current Trends and Existing Challenges. IEEE Access. 2021; 9 ():1-1.
Chicago/Turabian StylePrashant Singh; Maxim A. Dulebenets; Junayed Pasha; Ernesto D. R. Santibanez Gonzalez; Yui-Yip Lau; Raphael Kampmann. 2021. "Deployment of Autonomous Trains in Rail Transportation: Current Trends and Existing Challenges." IEEE Access 9, no. : 1-1.
In the absence of a specific treatment or vaccines, public health strategies are the main measures to use in the initial stages of a pandemic to allow surveillance of infectious diseases. During the ongoing global pandemic of coronavirus disease 2019 (COVID-19), several countries initiated various public health strategies, such as contact tracing and quarantine. The present study aims to conduct a systematic literature review to identify the presence of educational initiatives that promote the implementation of public health strategies before public health emergencies, with a special focus on contact tracing applications. Using Science Direct, PubMed, Scopus, and Gothenburg University search engines, all published scientific articles were included, while conference, reports, and non-scientific papers were excluded. The outcomes of the reviewed studies indicate that the effective implementation of public health strategies depends on the peoples’ willingness to participate and collaborate with local authorities. Several factors may influence such willingness, of which ethical, psychological, and practical factors seem to be the most important and frequently discussed. Moreover, individual willingness and readiness of a community may also vary based on the acquired level of knowledge about the incident and its cause and available management options. Educational initiatives, proper communication, and timely information at the community level were found to be the necessary steps to counteract misinformation and to promote a successful implementation of public health strategies and attenuate the effects of a pandemic. The systematic review conducted as a part of this study would benefit the relevant stakeholders and policy makers and assist with effective designing and implementation.
Amir Khorram-Manesh; Maxim Dulebenets; Krzysztof Goniewicz. Implementing Public Health Strategies—The Need for Educational Initiatives: A Systematic Review. International Journal of Environmental Research and Public Health 2021, 18, 5888 .
AMA StyleAmir Khorram-Manesh, Maxim Dulebenets, Krzysztof Goniewicz. Implementing Public Health Strategies—The Need for Educational Initiatives: A Systematic Review. International Journal of Environmental Research and Public Health. 2021; 18 (11):5888.
Chicago/Turabian StyleAmir Khorram-Manesh; Maxim Dulebenets; Krzysztof Goniewicz. 2021. "Implementing Public Health Strategies—The Need for Educational Initiatives: A Systematic Review." International Journal of Environmental Research and Public Health 18, no. 11: 5888.
The maritime transportation flows and container demand have been increasing over time, although the COVID-19 pandemic may slow down this trend for some time. One of the common strategies adopted by shipping lines to efficiently serve the existing customers is the deployment of large ships. The current practice in the liner shipping industry is to deploy a combination of ships of different types with different carrying capacities (i.e., heterogeneous fleet), especially at the routes with a significant demand. However, heterogeneous fleets of ships have been investigated by a very few studies addressing the tactical liner shipping decisions (i.e., determination of service frequency, ship fleet deployment, optimization of ship sailing speed, and design of ship schedules). Moreover, limited research efforts have been carried out to simultaneously capture all the major tactical liner shipping decisions using a single solution methodology. Therefore, this study proposes an integrated optimization model that addresses all the major tactical liner shipping decisions and allows the deployment of a heterogeneous ship fleet at each route, considering emissions generated throughout liner shipping operations. The model’s objective maximizes the total turnaround profit generated from liner shipping operations. A decomposition-based heuristic algorithm is presented in this study to solve the model proposed and efficiently tackle large-size problem instances. Numerical experiments, carried out for a number of real-world liner shipping routes, demonstrate the effectiveness of the proposed methodology. A set of managerial insights, obtained from the proposed methodology, are also provided.
Junayed Pasha; Maxim A. Dulebenets; Amir M. Fathollahi-Fard; Guangdong Tian; Yui-Yip Lau; Prashant Singh; Benbu Liang. An integrated optimization method for tactical-level planning in liner shipping with heterogeneous ship fleet and environmental considerations. Advanced Engineering Informatics 2021, 48, 101299 .
AMA StyleJunayed Pasha, Maxim A. Dulebenets, Amir M. Fathollahi-Fard, Guangdong Tian, Yui-Yip Lau, Prashant Singh, Benbu Liang. An integrated optimization method for tactical-level planning in liner shipping with heterogeneous ship fleet and environmental considerations. Advanced Engineering Informatics. 2021; 48 ():101299.
Chicago/Turabian StyleJunayed Pasha; Maxim A. Dulebenets; Amir M. Fathollahi-Fard; Guangdong Tian; Yui-Yip Lau; Prashant Singh; Benbu Liang. 2021. "An integrated optimization method for tactical-level planning in liner shipping with heterogeneous ship fleet and environmental considerations." Advanced Engineering Informatics 48, no. : 101299.
An efficient product distribution is critical for proper supply chain operations. Many supply chains handle perishable products that decay over time. Due to mismanagement of supply chain operations, a significant portion of perishable products is wasted, resulting in substantial monetary losses. Cross-docking terminals (CDTs) have been widely used in cold supply chains for the product distribution but have not received adequate attention in the scientific literature. To improve the efficiency of perishable product distribution, this study introduces for the first time a novel mixed-integer mathematical formulation for the truck scheduling optimization at a cold-chain CDT. The model explicitly captures the decay of perishable products throughout the service of arriving trucks and accounts for the presence of temperature-controlled storage areas that are specifically designated for perishable products. The objective minimizes the total cost incurred during the truck service. Considering the complexity of the proposed model, a customized Evolutionary Algorithm is developed to solve it. The computational performance of the developed algorithm is assessed throughout the numerical experiments based on a detailed comparative analysis against the other metaheuristics. The developed Evolutionary Algorithm is found to be the most promising metaheuristic, considering both solution quality and CPU time perspectives. Furthermore, the proposed algorithm demonstrates an acceptable stability of the solution quality at termination. A set of additional sensitivity analyses are performed in order to draw some significant managerial implications, which would be of potential interest to the supply chain stakeholders that are involved in the distribution of perishable products in cold supply chains.
Oluwatosin Theophilus; Maxim A. Dulebenets; Junayed Pasha; Yui-Yip Lau; Amir M. Fathollahi-Fard; Arash Mazaheri. Truck scheduling optimization at a cold-chain cross-docking terminal with product perishability considerations. Computers & Industrial Engineering 2021, 156, 107240 .
AMA StyleOluwatosin Theophilus, Maxim A. Dulebenets, Junayed Pasha, Yui-Yip Lau, Amir M. Fathollahi-Fard, Arash Mazaheri. Truck scheduling optimization at a cold-chain cross-docking terminal with product perishability considerations. Computers & Industrial Engineering. 2021; 156 ():107240.
Chicago/Turabian StyleOluwatosin Theophilus; Maxim A. Dulebenets; Junayed Pasha; Yui-Yip Lau; Amir M. Fathollahi-Fard; Arash Mazaheri. 2021. "Truck scheduling optimization at a cold-chain cross-docking terminal with product perishability considerations." Computers & Industrial Engineering 156, no. : 107240.
Industrialization, urban development, and population growth in the last decades caused a significant increase in congestion of transportation networks across the world. Increasing congestion of transportation networks and limitations of the traditional methods in analyzing and evaluating the congestion mitigation strategies led many transportation professionals to the use of traffic simulation techniques. Nowadays, traffic simulation is heavily used in a variety of applications, including the design of transportation facilities, traffic flow management, and intelligent transportation systems. The literature review, conducted as a part of this study, shows that many different traffic simulation packages with various features have been developed to date. The present study specifically focuses on a comprehensive comparative analysis of the advanced interactive microscopic simulator for urban and non-urban networks (AIMSUN) and SimTraffic microsimulation models, which have been widely used in the literature and practice. The evaluation of microsimulation models is performed for the four roadway sections with different functional classifications, which are located in the northern part of Iran. The SimTraffic and AIMSUN microsimulation models are compared in terms of the major transportation network performance indicators. The results from the conducted analysis indicate that AIMSUN returned smaller errors for the vehicle flow, travel speed, and total travel distance. On the other hand, SimTraffic provided more accurate values of the travel time. Both microsimulation models were able to effectively identify traffic bottlenecks. Findings from this study will be useful for the researchers and practitioners, who heavily rely on microsimulation models in transportation planning.
Amir Rahimi; Maxim Dulebenets; Arash Mazaheri. Evaluation of Microsimulation Models for Roadway Segments with Different Functional Classifications in Northern Iran. Infrastructures 2021, 6, 46 .
AMA StyleAmir Rahimi, Maxim Dulebenets, Arash Mazaheri. Evaluation of Microsimulation Models for Roadway Segments with Different Functional Classifications in Northern Iran. Infrastructures. 2021; 6 (3):46.
Chicago/Turabian StyleAmir Rahimi; Maxim Dulebenets; Arash Mazaheri. 2021. "Evaluation of Microsimulation Models for Roadway Segments with Different Functional Classifications in Northern Iran." Infrastructures 6, no. 3: 46.
Many supply chain stakeholders rely on the cross-docking concept, according to which products delivered in specific transportation management units to the cross-docking terminal (CDT) undergo decomposition, sorting based on the end customer preferences, consolidation, and then transported to the final destinations. Scheduling of the inbound and outbound trucks for service at the CDT doors is considered as one of the convoluted decision problems faced by the CDT operators. This study proposes a new Adaptive Polyploid Memetic Algorithm (APMA) for the problem of scheduling CDT trucks that can assist with proper CDT operations planning. APMA directly relies on the polyploidy concept, where copies of the parent chromosomes (i.e., solutions) are stored before performing the crossover operations and producing the offspring chromosomes. The number of chromosome copies is controlled through the adaptive polyploid mechanism based on the objective function improvements achieved and computational time changes. Moreover, a number of problem-specific hybridization techniques are used within the algorithm to facilitate the search process. Computational experiments show that the application of adaptive polyploidy alone may not be sufficient for the considered decision problem. Hybridization techniques that directly consider problem-specific properties are required in order to improve solution quality at convergence. Furthermore, the APMA algorithm developed in this article substantially outperforms some of the well-known state of the art metaheuristics with regards to solution quality and returns truck schedules that have lower total truck service cost.
Maxim A. Dulebenets. An Adaptive Polyploid Memetic Algorithm for scheduling trucks at a cross-docking terminal. Information Sciences 2021, 565, 390 -421.
AMA StyleMaxim A. Dulebenets. An Adaptive Polyploid Memetic Algorithm for scheduling trucks at a cross-docking terminal. Information Sciences. 2021; 565 ():390-421.
Chicago/Turabian StyleMaxim A. Dulebenets. 2021. "An Adaptive Polyploid Memetic Algorithm for scheduling trucks at a cross-docking terminal." Information Sciences 565, no. : 390-421.
Social distancing is one of the most recommended policies worldwide to reduce diffusion risk during the COVID-19 pandemic. Based on a risk management perspective, this study explores the mechanism of the risk perception effect on social distancing in order to improve individual physical distancing behavior. The data for this study were collected from 317 Chinese residents in May 2020 using an internet-based survey. A structural equation model (SEM) and hierarchical linear regression (HLR) analyses were conducted to examine all the considered research hypotheses. The results show that risk perception significantly affects perceived understanding and social distancing behaviors in a positive way. Perceived understanding has a significant positive correlation with social distancing behaviors and plays a mediating role in the relationship between risk perception and social distancing behaviors. Furthermore, safety climate positively predicts social distancing behaviors but lessens the positive correlation between risk perception and social distancing. Hence, these findings suggest effective management guidelines for successful implementation of the social distancing policies during the COVID-19 pandemic by emphasizing the critical role of risk perception, perceived understanding, and safety climate.
Kefan Xie; Benbu Liang; Maxim A. Dulebenets; Yanlan Mei. The Impact of Risk Perception on Social Distancing during the COVID-19 Pandemic in China. International Journal of Environmental Research and Public Health 2020, 17, 6256 .
AMA StyleKefan Xie, Benbu Liang, Maxim A. Dulebenets, Yanlan Mei. The Impact of Risk Perception on Social Distancing during the COVID-19 Pandemic in China. International Journal of Environmental Research and Public Health. 2020; 17 (17):6256.
Chicago/Turabian StyleKefan Xie; Benbu Liang; Maxim A. Dulebenets; Yanlan Mei. 2020. "The Impact of Risk Perception on Social Distancing during the COVID-19 Pandemic in China." International Journal of Environmental Research and Public Health 17, no. 17: 6256.
Highway–rail grade crossings (HRGCs) are one of the most dangerous segments of the transportation network. Every year numerous accidents are recorded at HRGCs between highway users and trains, between highway users and traffic control devices, and solely between highway users. These accidents cause fatalities, severe injuries, property damage, and release of hazardous materials. Researchers and state Departments of Transportation (DOTs) have addressed safety concerns at HRGCs in the USA by investigating the factors that may cause accidents at HRGCs and developed certain accident and hazard prediction models to forecast the occurrence of accidents and crossing vulnerability. The accident and hazard prediction models are used to identify the most hazardous HRGCs that require safety improvements. This study provides an extensive review of the state-of-the-practice to identify the existing accident and hazard prediction formulae that have been used over the years by different state DOTs. Furthermore, this study analyzes the common factors that have been considered in the existing accident and hazard prediction formulae. The reported performance and implementation challenges of the identified accident and hazard prediction formulae are discussed in this study as well. Based on the review results, the US DOT Accident Prediction Formula was found to be the most commonly used formula due to its accuracy in predicting the number of accidents at HRGCs. However, certain states still prefer customized models due to some practical considerations. Data availability and data accuracy were identified as some of the key model implementation challenges in many states across the country.
Olumide F. Abioye; Maxim A. Dulebenets; Junayed Pasha; Masoud Kavoosi; Ren Moses; John Sobanjo; Eren E. Ozguven. Accident and hazard prediction models for highway–rail grade crossings: a state-of-the-practice review for the USA. Railway Engineering Science 2020, 28, 251 -274.
AMA StyleOlumide F. Abioye, Maxim A. Dulebenets, Junayed Pasha, Masoud Kavoosi, Ren Moses, John Sobanjo, Eren E. Ozguven. Accident and hazard prediction models for highway–rail grade crossings: a state-of-the-practice review for the USA. Railway Engineering Science. 2020; 28 (3):251-274.
Chicago/Turabian StyleOlumide F. Abioye; Maxim A. Dulebenets; Junayed Pasha; Masoud Kavoosi; Ren Moses; John Sobanjo; Eren E. Ozguven. 2020. "Accident and hazard prediction models for highway–rail grade crossings: a state-of-the-practice review for the USA." Railway Engineering Science 28, no. 3: 251-274.
The “factory-in-a-box” concept involves assembling production modules (i.e., factories) in containers and transporting the containers to different customer locations. Such a concept could be highly effective during emergencies, when there is an urgent demand for products (e.g., the COVID-19 pandemic). The “factory-in-a-box” planning problem can be divided into two sub-problems. The first sub-problem deals with the assignment of raw materials to suppliers, sub-assembly decomposition, assignment of sub-assembly modules to manufacturers, and assignment of tasks to manufacturers. The second sub-problem focuses on the transport of sub-assembly modules between suppliers and manufacturers by assigning vehicles to locations, deciding the order of visits for suppliers, manufacturers, and customers, and selecting the appropriate routes within the transportation network. This study addresses the second sub-problem, which resembles the vehicle routing problem, by developing an optimization model and solution algorithms in order to optimize the “factory-in-a-box” supply chain. A mixed-integer linear programming model, which aims to minimize the total cost of the “factory-in-a-box” supply chain, is presented in this study. CPLEX is used to solve the model to the global optimality, while four metaheuristic algorithms, including the Evolutionary Algorithm, Variable Neighborhood Search, Tabu Search, and Simulated Annealing, are employed to solve the model for large-scale problem instances. A set of numerical experiments, conducted for a case study of “factory-in-a-box”, demonstrate that the Evolutionary Algorithm outperforms the other metaheuristic algorithms developed for the model. Some managerial insights are outlined in the numerical experiments as well.
Junayed Pasha; Maxim A. Dulebenets; Masoud Kavoosi; Olumide F. Abioye; Hui Wang; Weihong Guo. An Optimization Model and Solution Algorithms for the Vehicle Routing Problem With a “Factory-in-a-Box”. IEEE Access 2020, 8, 134743 -134763.
AMA StyleJunayed Pasha, Maxim A. Dulebenets, Masoud Kavoosi, Olumide F. Abioye, Hui Wang, Weihong Guo. An Optimization Model and Solution Algorithms for the Vehicle Routing Problem With a “Factory-in-a-Box”. IEEE Access. 2020; 8 (99):134743-134763.
Chicago/Turabian StyleJunayed Pasha; Maxim A. Dulebenets; Masoud Kavoosi; Olumide F. Abioye; Hui Wang; Weihong Guo. 2020. "An Optimization Model and Solution Algorithms for the Vehicle Routing Problem With a “Factory-in-a-Box”." IEEE Access 8, no. 99: 134743-134763.
The sinking of the Titanic has brought cruise ship safety onto the international agenda. However, different shipwrecks have been occurring in the cruise industry with relatively high frequency for more than one century due to human errors. In order to improve cruise ship safety, the International Maritime Organization and the Cruise Lines International Association introduced a set of safety enhancement policies and measurements. However, the expansion of ships and fairly weak safety regulations continue to pose risks of human life loss during cruise ship accidents, particularly in Asian regions. Asian countries have been constantly implementing various safety measures, but serious cruise ship accidents still occur from time to time, even after significant past experiences. Are the cruise ship accidents predominantly the result of human failures and organizational factors? This paper undertakes a detailed historical review of cruise ship accidents since 1972 through an intensive overview of the documents published by the Safety of Life at Sea (SOLAS) Convention and the Maritime Safety Committee. Furthermore, a set of case studies of representative cruise ship accidents are conducted as a part of this study. The outcomes of this study will help cruise shipping companies to better understand the factors influencing cruise ship accident occurrence and to construct appropriate safety policy measures, aiming to prevent cruise ship accidents in Asian regions.
Yue Jiao; Maxim A. Dulebenets; Yui-Yip Lau. Cruise Ship Safety Management in Asian Regions: Trends and Future Outlook. Sustainability 2020, 12, 5567 .
AMA StyleYue Jiao, Maxim A. Dulebenets, Yui-Yip Lau. Cruise Ship Safety Management in Asian Regions: Trends and Future Outlook. Sustainability. 2020; 12 (14):5567.
Chicago/Turabian StyleYue Jiao; Maxim A. Dulebenets; Yui-Yip Lau. 2020. "Cruise Ship Safety Management in Asian Regions: Trends and Future Outlook." Sustainability 12, no. 14: 5567.
This paper proposes a structure for sustainable implementation of urban distribution centers (UDCs) in historical cities, considering the opinion of the main stakeholders involved in the urban distribution of goods and a set of additional criteria. Based on a survey that was conducted among carriers, traffic wardens, and retailers, a decision hierarchy structure, consisting of the relevant criteria evaluated by various statistical techniques, will be used for sustainable implementation of UDCs. The methodology uses a database collected in the historical center of Ouro Preto, a Brazilian city which contains common characteristics of other Latin American and some European cities that are included in the World Heritage List. This structure is unique, as it is based on a survey among the main stakeholders, and can be applied by logistics operators and local authorities for implementing UDCs to address urban distribution issues, especially in historical cities. However, without loss of generality, the proposed methodology can be adopted for different cities using the appropriate criteria according to the characteristics of the cities.
Nayara De Carvalho; José Vieira; Paula Da Fonseca; Maxim Dulebenets. A Multi-Criteria Structure for Sustainable Implementation of Urban Distribution Centers in Historical Cities. Sustainability 2020, 12, 5538 .
AMA StyleNayara De Carvalho, José Vieira, Paula Da Fonseca, Maxim Dulebenets. A Multi-Criteria Structure for Sustainable Implementation of Urban Distribution Centers in Historical Cities. Sustainability. 2020; 12 (14):5538.
Chicago/Turabian StyleNayara De Carvalho; José Vieira; Paula Da Fonseca; Maxim Dulebenets. 2020. "A Multi-Criteria Structure for Sustainable Implementation of Urban Distribution Centers in Historical Cities." Sustainability 12, no. 14: 5538.
Disruption occurrences in liner shipping operations affect schedule reliability and may increase the total cost of delivering cargoes at ports. If a vessel experiences disruption occurrences either at ports of call or in sea, the liner shipping company is required to decide on the schedule recovery action to execute in order to recover the resulting delays. This study formulates a novel mathematical model for the vessel schedule recovery problem (VSRP) in liner shipping. The objective aims to minimize the total profit loss, suffered by the liner shipping company due to disruption occurrences at a given liner shipping route. A total of four recovery strategies are considered in the model, which include: (1) vessel sailing speed adjustment; (2) vessel handling rate adjustment; (3) port skipping without container diversion; and (4) port skipping with container diversion. The proposed mathematical formulation for the nonlinear VSRP model is solved to the global optimality using BARON. A set of computational experiments are further performed for the Middle East/Pakistan/India-West Mediterranean (WM3) route, which is served by the OOCL liner shipping company, for various scenarios of disruption occurrences in sea and at ports. The results from the performed analyses demonstrate potential benefits for liner shipping companies from using the proposed methodology for various realistic scenarios of disruptions.
Olumide F. Abioye; Maxim A. Dulebenets; Masoud Kavoosi; Junayed Pasha; Oluwatosin Theophilus. Vessel Schedule Recovery in Liner Shipping: Modeling Alternative Recovery Options. IEEE Transactions on Intelligent Transportation Systems 2020, 1 -15.
AMA StyleOlumide F. Abioye, Maxim A. Dulebenets, Masoud Kavoosi, Junayed Pasha, Oluwatosin Theophilus. Vessel Schedule Recovery in Liner Shipping: Modeling Alternative Recovery Options. IEEE Transactions on Intelligent Transportation Systems. 2020; (99):1-15.
Chicago/Turabian StyleOlumide F. Abioye; Maxim A. Dulebenets; Masoud Kavoosi; Junayed Pasha; Oluwatosin Theophilus. 2020. "Vessel Schedule Recovery in Liner Shipping: Modeling Alternative Recovery Options." IEEE Transactions on Intelligent Transportation Systems , no. 99: 1-15.
Accidents at highway-rail grade crossings can cause fatalities and injuries, as well as significant property damages. In order to prevent accidents, certain upgrades need to be made at highway-rail grade crossings. However, due to limited monetary resources, only the most hazardous highway-rail grade crossings should receive a priority for upgrading. Hence, accident/hazard prediction models are required to identify the most hazardous highway-rail grade crossings for safety improvement projects. This study selects and evaluates the accident and hazard prediction models found in the highway-rail grade crossing safety literature to rank the highway-rail grade crossings in the State of Florida. Three approaches are undertaken to evaluate the candidate accident and hazard prediction models, including the chi-square statistic, grouping of crossings based on the actual accident data, and Spearman rank correlation coefficient. The analysis was conducted for the 589 highway-rail grade crossings located in the State of Florida using the data available through the highway-rail grade crossing inventory database maintained by the Federal Railroad Administration. As a result of the performed analysis, a new hazard prediction model, named as the Florida Priority Index Formula, is recommended to rank/prioritize the highway-rail grade crossings in the State of Florida. The Florida Priority Index Formula provides a more accurate ranking of highway-rail grade crossings as compared to the alternative methods. The Florida Priority Index Formula assesses the potential hazard of a given highway-rail grade crossing based on the average daily traffic volume, average daily train volume, train speed, existing traffic control devices, accident history, and crossing upgrade records.
Junayed Pasha; Maxim A. Dulebenets; Olumide F. Abioye; Masoud Kavoosi; Ren Moses; John Sobanjo; Eren E. Ozguven. A Comprehensive Assessment of the Existing Accident and Hazard Prediction Models for the Highway-Rail Grade Crossings in the State of Florida. Sustainability 2020, 12, 4291 .
AMA StyleJunayed Pasha, Maxim A. Dulebenets, Olumide F. Abioye, Masoud Kavoosi, Ren Moses, John Sobanjo, Eren E. Ozguven. A Comprehensive Assessment of the Existing Accident and Hazard Prediction Models for the Highway-Rail Grade Crossings in the State of Florida. Sustainability. 2020; 12 (10):4291.
Chicago/Turabian StyleJunayed Pasha; Maxim A. Dulebenets; Olumide F. Abioye; Masoud Kavoosi; Ren Moses; John Sobanjo; Eren E. Ozguven. 2020. "A Comprehensive Assessment of the Existing Accident and Hazard Prediction Models for the Highway-Rail Grade Crossings in the State of Florida." Sustainability 12, no. 10: 4291.
The devastating impacts of natural hazards, including loss of lives and properties, underline the importance of efficient hazard preparedness, especially in the areas with frequent hazard occurrence. Several studies indicated that driving during emergency evacuation is quite challenging due to dense traffic flow, inclement weather conditions, and unexpected maneuvers of other evacuees. However, limited research has been directed towards assessing the perceived driving difficulties of individuals, including vulnerable population, under emergency evacuation. This study deploys a driving simulator in order to emulate realistic emergency evacuation scenarios and to quantify the perceived driving difficulties of individuals under emergency evacuation. Based on the data, collected using a driving simulator, a number of statistical models is proposed to determine a set of performance indicators, including the mental demand, physical demand, temporal demand, performance, effort, and frustration, experienced by individuals as a result of emergency evacuation. The statistical models also capture a variety of different driver characteristics, traffic characteristics, driving conditions, and evacuation route characteristics. The analysis results suggest that the considered performance indicators are significantly influenced with a number of factors, including age, gender, education, race, presence of chronic diseases, and self-reported driving ability. The insights from the conducted research can be applied at the hazard preparedness stage to mitigate the perceived driving difficulties of individuals under emergency evacuation and ensure their safety.
Olumide F. Abioye; Maxim A. Dulebenets; Eren Erman Ozguven; Ren Moses; Walter R. Boot; Thobias Sando. Assessing perceived driving difficulties under emergency evacuation for vulnerable population groups. Socio-Economic Planning Sciences 2020, 72, 100878 .
AMA StyleOlumide F. Abioye, Maxim A. Dulebenets, Eren Erman Ozguven, Ren Moses, Walter R. Boot, Thobias Sando. Assessing perceived driving difficulties under emergency evacuation for vulnerable population groups. Socio-Economic Planning Sciences. 2020; 72 ():100878.
Chicago/Turabian StyleOlumide F. Abioye; Maxim A. Dulebenets; Eren Erman Ozguven; Ren Moses; Walter R. Boot; Thobias Sando. 2020. "Assessing perceived driving difficulties under emergency evacuation for vulnerable population groups." Socio-Economic Planning Sciences 72, no. : 100878.
Smart cities directly rely on a variety of elements, including water, gas, electricity, buildings, services, transportation networks, and others. Lack of properly designed transportation networks may cause different economic and safety concerns. Highway–rail grade crossings are known to be a hazardous point in the transportation network, considering a remarkable number of accidents recorded annually between highway users and trains, and even solely between highway users at highway–rail grade crossings. Hence, safety improvement at highway–rail grade crossings is a challenging issue for smart city authorities, given limitations in monetary resources. In this study, two optimization models are developed for resource allocation among highway–rail grade crossings to minimize the overall hazard and the overall hazard severity, taking into account the available budget limitations. The optimization models are solved by CPLEX to the global optimality. Moreover, some heuristic algorithms are proposed as well. A case study focusing on the public highway–rail grade crossings in the State of Florida is performed to evaluate the effectiveness of the developed optimization models and the solution methodologies. In terms of the computational time, all the solution approaches are found to be effective decision support tools from the practical standpoint. Moreover, the results demonstrate that some of the developed heuristic algorithms can provide near-optimal solutions. Therefore, the smart city authorities can utilize the proposed heuristics as decision support tools for effective resource allocation among highway–rail grade crossings.
Masoud Kavoosi; Maxim A. Dulebenets; Junayed Pasha; Olumide F. Abioye; Ren Moses; John Sobanjo; Eren E. Ozguven. Development of Algorithms for Effective Resource Allocation among Highway–Rail Grade Crossings: A Case Study for the State of Florida. Energies 2020, 13, 1419 .
AMA StyleMasoud Kavoosi, Maxim A. Dulebenets, Junayed Pasha, Olumide F. Abioye, Ren Moses, John Sobanjo, Eren E. Ozguven. Development of Algorithms for Effective Resource Allocation among Highway–Rail Grade Crossings: A Case Study for the State of Florida. Energies. 2020; 13 (6):1419.
Chicago/Turabian StyleMasoud Kavoosi; Maxim A. Dulebenets; Junayed Pasha; Olumide F. Abioye; Ren Moses; John Sobanjo; Eren E. Ozguven. 2020. "Development of Algorithms for Effective Resource Allocation among Highway–Rail Grade Crossings: A Case Study for the State of Florida." Energies 13, no. 6: 1419.
A large-scale emergency evacuation due to an approaching natural disaster requires local and state administrations to make important decisions regarding evacuation routes, emergency shelters, and evacuation time periods, among other things. Considering a conflicting nature of certain emergency evacuation planning decisions, this study introduces a multiobjective optimization model for emergency evacuation planning that aims to minimize a set of critical performance indicators, including the total evacuation time, mental demand, physical demand, temporal demand, effort, and frustration endured by the individuals evacuating from a given metropolitan area anticipating a natural disaster. The major driver characteristics, evacuation route characteristics, driving conditions, and traffic characteristics that affect the driving performance of individuals, including vulnerable population groups, are incorporated in the proposed mathematical model. In order to solve the developed mathematical model and analyze the trade-offs among the conflicting objectives, this study presents four multiobjective heuristic algorithms. The computational experiments were conducted using real-world data and showcase the efficiency of the proposed methodology. The developed multiobjective methodology is expected to improve the safety of evacuees at the natural disaster preparedness stage and ensure timely evacuation from areas expecting significant natural disaster impacts.
Maxim A. Dulebenets; Junayed Pasha; Masoud Kavoosi; Olumide F. Abioye; Eren E. Ozguven; Ren Moses; Walter R. Boot; Thobias Sando. Multiobjective Optimization Model for Emergency Evacuation Planning in Geographical Locations with Vulnerable Population Groups. Journal of Management in Engineering 2020, 36, 04019043 .
AMA StyleMaxim A. Dulebenets, Junayed Pasha, Masoud Kavoosi, Olumide F. Abioye, Eren E. Ozguven, Ren Moses, Walter R. Boot, Thobias Sando. Multiobjective Optimization Model for Emergency Evacuation Planning in Geographical Locations with Vulnerable Population Groups. Journal of Management in Engineering. 2020; 36 (2):04019043.
Chicago/Turabian StyleMaxim A. Dulebenets; Junayed Pasha; Masoud Kavoosi; Olumide F. Abioye; Eren E. Ozguven; Ren Moses; Walter R. Boot; Thobias Sando. 2020. "Multiobjective Optimization Model for Emergency Evacuation Planning in Geographical Locations with Vulnerable Population Groups." Journal of Management in Engineering 36, no. 2: 04019043.
Liner shipping plays a major role for freight transportation and international seaborne trade. The economic development of different countries is significantly dependent on the movement of a containerized cargo. One of the most challenging decision problems, tackled by liner shipping companies, is the design of vessel schedules. At the vessel scheduling stage, the liner shipping company aims to determine vessel sailing speeds at voyage legs of a given liner shipping route, port times, vessel handling rates at ports, the minimum number of vessels required in order to provide the agreed service frequency at ports, and other factors. Considering the existing pollution levels, the environmental impacts of liner shipping have to be captured in the vessel scheduling models as well. This study conducts a comprehensive survey of the existing research on vessel scheduling in liner shipping. The collected vessel scheduling studies are classified into different categories, including general vessel scheduling, uncertainty in liner shipping operations, collaborative agreements, vessel schedule recovery, and green liner shipping. Based on a detailed analysis of the collected literature, findings are discussed, and limitations in the state-of-the-art are identified for each category of studies. The study concludes with a number of future research opportunities, taking into account the recent developments and trends in liner shipping.
Maxim A. Dulebenets; Junayed Pasha; Olumide Abioye; Masoud Kavoosi. Vessel scheduling in liner shipping: a critical literature review and future research needs. Flexible Services and Manufacturing Journal 2019, 33, 43 -106.
AMA StyleMaxim A. Dulebenets, Junayed Pasha, Olumide Abioye, Masoud Kavoosi. Vessel scheduling in liner shipping: a critical literature review and future research needs. Flexible Services and Manufacturing Journal. 2019; 33 (1):43-106.
Chicago/Turabian StyleMaxim A. Dulebenets; Junayed Pasha; Olumide Abioye; Masoud Kavoosi. 2019. "Vessel scheduling in liner shipping: a critical literature review and future research needs." Flexible Services and Manufacturing Journal 33, no. 1: 43-106.
Recent trends in the management of supply chains have witnessed an increasing implementation of the cross-docking strategy. The cross-docking strategy, being the one that can potentially improve supply chain operations, has received a lot of attention from researchers in recent years, especially over the last decade. Cross-docking involves the reception of inbound products, deconsolidation, sorting, consolidation, and shipping of the consolidated products to the end customers. The number of research efforts, aiming to study and improve the cross-docking operations, increases every year. While some studies discuss cross-docking as an integral part of a supply chain, other studies focus on the ways of making cross-docking terminals more efficient and propose different operations research techniques for various decision problems at cross-docking terminals. In order to identify the recent cross-docking trends, this study performs a state-of-the-art review with a particular focus on the truck scheduling problem at cross-docking terminals. A comprehensive evaluation of the reviewed studies is conducted, focusing on the major attributes of the cross-docking operations. These attributes include terminal shape considered, doors considered, door service mode considered, preemption, internal transportation mode used, temporary storage capacity, resource capacity, objectives considered, and solution methods adopted. Based on findings from the review of studies, some common issues are outlined and future research directions are proposed.
Oluwatosin Theophilus; Maxim A. Dulebenets; Junayed Pasha; Olumide F. Abioye; Masoud Kavoosi. Truck Scheduling at Cross-Docking Terminals: A Follow-Up State-Of-The-Art Review. Sustainability 2019, 11, 5245 .
AMA StyleOluwatosin Theophilus, Maxim A. Dulebenets, Junayed Pasha, Olumide F. Abioye, Masoud Kavoosi. Truck Scheduling at Cross-Docking Terminals: A Follow-Up State-Of-The-Art Review. Sustainability. 2019; 11 (19):5245.
Chicago/Turabian StyleOluwatosin Theophilus; Maxim A. Dulebenets; Junayed Pasha; Olumide F. Abioye; Masoud Kavoosi. 2019. "Truck Scheduling at Cross-Docking Terminals: A Follow-Up State-Of-The-Art Review." Sustainability 11, no. 19: 5245.