This page has only limited features, please log in for full access.
Prof. Ali AlArjani has worked as a professor in the Dept of Mechanical and Industrial Engineering, Prince Sattam bin Abdulaziz University, Saudi Arabia, for the last ten years. He has extensive experience in research and conducting projects in supply chain management. Several research articles have been published in numerous peer-reviewed journals.
Achieving sustainable development goals agenda 2030 is the aspiration of all the United Nation’s member countries. Countries have an uneven distribution of natural resources, economic strength, and capacity building. Many studies analyze these goals using various models and considering different aspects of the kingdom of Saudi Arabia's (KSA) economy. However, none of the studies modelled the key indicators mathematically to quantify the achievement level towards vision 2030; hence aims to bridge the existing literature gap In this paper, the sustainable development goals (SDGs) of KSA are considered, a mathematical model is formulated in light of fuzzy and weighted goal programming using membership function. The model comprises three goals related to the gross domestic product, sustainable energy consumption and employment capacity of the economy's contributing sectors. The analytic hierarchy process integrated to compute the goals’ weights using row geometric mean method. The study established the goals's satisfaction level with 57% overall achievement of the vision 2030. Individually, economic growth goal is 45% achievable. The clean energy consumption-related goal is 67% realizable. The employment-related goal is 78% attainable within the time frame of the vision 2030. The study suggests that KSA diversify its energy sector by concentrating and investing more resources in alternative energy sources, including renewable energy such as solar, wind, biomass, and nuclear energy. Also, there is a need to involve more vibrant and talented youths in the critical decision-making process. The model is simple and can be replicable in a similar country with slight modifications.
Ali AlArjani; Umar Muhammad Modibbo; Irfan Ali; Biswajit Sarkar. A new framework for the sustainable development goals of Saudi Arabia. Journal of King Saud University - Science 2021, 33, 101477 .
AMA StyleAli AlArjani, Umar Muhammad Modibbo, Irfan Ali, Biswajit Sarkar. A new framework for the sustainable development goals of Saudi Arabia. Journal of King Saud University - Science. 2021; 33 (6):101477.
Chicago/Turabian StyleAli AlArjani; Umar Muhammad Modibbo; Irfan Ali; Biswajit Sarkar. 2021. "A new framework for the sustainable development goals of Saudi Arabia." Journal of King Saud University - Science 33, no. 6: 101477.
Recycling of products has a great impact on contemporary sustainable business strategies. In this study, a sustainable recycling process in a production-inventory model for an imperfect production system with a fixed ratio of recyclable defective products is introduced. The piecewise constant demand rates of the non-defective items are considered under production run-time, production off-time with positive stock, and production off-time with shortages under varying conditions. Based on the production process, two cases are studied using this model. The first case does not consider recycling processes, while the second case picks up all defective items before sending these items to recycling during the production off-time; the recycled items are added to the main inventory. The aim of this study is to minimize the total cost and identify the optimal order quantity. The manufacturing process with the recycling process provides a better result compared to without recycling in the first case. Some theoretical derivations are developed to enunciate the objective function using the classical optimization technique. To validate the proposed study, sensitivity analysis is performed, and numerical examples are given. Finally, some managerial insights and the scope of future research are provided.
Ali AlArjani; Maniruzzaman Miah; Sharif Uddin; Abu Mashud; Hui-Ming Wee; Shib Sana; Hari Srivastava. A Sustainable Economic Recycle Quantity Model for Imperfect Production System with Shortages. Journal of Risk and Financial Management 2021, 14, 173 .
AMA StyleAli AlArjani, Maniruzzaman Miah, Sharif Uddin, Abu Mashud, Hui-Ming Wee, Shib Sana, Hari Srivastava. A Sustainable Economic Recycle Quantity Model for Imperfect Production System with Shortages. Journal of Risk and Financial Management. 2021; 14 (4):173.
Chicago/Turabian StyleAli AlArjani; Maniruzzaman Miah; Sharif Uddin; Abu Mashud; Hui-Ming Wee; Shib Sana; Hari Srivastava. 2021. "A Sustainable Economic Recycle Quantity Model for Imperfect Production System with Shortages." Journal of Risk and Financial Management 14, no. 4: 173.
Every industry always tries to provide the best service to its consumers. To provide better service to the consumer and optimize profit, a sustainable online-to-offline retailing strategy is proposed in this current study. Both online and offline systems are considered here, i.e., to provide the best service, the industry sells its products online and offline. Due to the consideration of online and offline systems, the selling price of the products is also different for different modes, and the demand for a particular product is the combined demand of online demand and offline demand, which depend on the selling price of the product. Moreover, the exact lead time and exact backorder are calculated to obtain the system’s exact cost or profit, which directly improves the system’s service. Different investments are incorporated to optimize the total system profit. A distribution-free approach is utilized to solve this model. Numerical examples are provided to prove the applicability of the model in reality. Sensitivity analysis is performed based on critical parameters. Special cases and graphical representations also prove the global optimality of the current study.
Biswajit Sarkar; Bikash Dey; Mitali Sarkar; Ali AlArjani. A Sustainable Online-to-Offline (O2O) Retailing Strategy for a Supply Chain Management under Controllable Lead Time and Variable Demand. Sustainability 2021, 13, 1756 .
AMA StyleBiswajit Sarkar, Bikash Dey, Mitali Sarkar, Ali AlArjani. A Sustainable Online-to-Offline (O2O) Retailing Strategy for a Supply Chain Management under Controllable Lead Time and Variable Demand. Sustainability. 2021; 13 (4):1756.
Chicago/Turabian StyleBiswajit Sarkar; Bikash Dey; Mitali Sarkar; Ali AlArjani. 2021. "A Sustainable Online-to-Offline (O2O) Retailing Strategy for a Supply Chain Management under Controllable Lead Time and Variable Demand." Sustainability 13, no. 4: 1756.
Selective maintenance problem plays an essential role in reliability optimization decision-making problems. Systems are a configuration of several components, and there are situations the system needs small intervals or break for maintenance actions, during the intervals expert carried out the maintenance actions to replace or repair the deteriorated components of the systems. Because of the uncertainty associated with the component’s operational time, failure, and next mission duration create a new challenge in determining optimal components allocation and evaluating future missions successfully. In this paper, a multi-objective selective maintenance allocation problem is formulated with fuzzy parameters under neutrosophic environment. A new defuzzification technique is introduced based on beta distribution to convert fuzzy parameters into crisp values. The neutrosophic goal programming technique is used to determine the compromise allocation of replaceable and repairable components based on the system reliability optimization. A numerical illustration is used to validate the model and ascertain its effectiveness. The result is compared with two other approaches and found to be better. The method is flexible and straightforward and can be solved using any available commercial packages. The extension of the concept can be useful to other complex system reliability optimization.
Murshid Kamal; Umar Muhammad Modibbo; Ali AlArjani; Irfan Ali. Neutrosophic fuzzy goal programming approach in selective maintenance allocation of system reliability. Complex & Intelligent Systems 2021, 7, 1045 -1059.
AMA StyleMurshid Kamal, Umar Muhammad Modibbo, Ali AlArjani, Irfan Ali. Neutrosophic fuzzy goal programming approach in selective maintenance allocation of system reliability. Complex & Intelligent Systems. 2021; 7 (2):1045-1059.
Chicago/Turabian StyleMurshid Kamal; Umar Muhammad Modibbo; Ali AlArjani; Irfan Ali. 2021. "Neutrosophic fuzzy goal programming approach in selective maintenance allocation of system reliability." Complex & Intelligent Systems 7, no. 2: 1045-1059.
In a managerial position, the ultimate objective is to take the right decision for the decision maker (DM) when transportation parameters are uncertain due to the globalization and other uncontrollable influences. In this paper, fuzzy membership function tactic based on goal programming to obtain the desired compromise solution of a multi-objective transportation problem (MOTP) in uncertain environment is proposed where the DM can choose a confidence level for different parameters. On the basis of DM’s choice on a particular confidence level, a compromise solution is obtain indicating the satisfaction level of the DM if the problem is feasible for this chosen confidence level. Uncertain normal distribution is used to convert the parameters from uncertain to a certain one. Simple linear programming problem (LPP) is designed using fuzzy linear membership function where the upper and lower values of the objectives are the desired goals of the DM. A numerical illustration is furnished to establish the effectiveness of the designed model whereas the single objective transportation problems are solved by TORA and LPPs are solved by using LINGO for operations research.
Sharif Uddin; Musa Miah; Al-Amin Khan; Ali AlArjani. Goal programming tactic for uncertain multi-objective transportation problem using fuzzy linear membership function. Alexandria Engineering Journal 2021, 60, 2525 -2533.
AMA StyleSharif Uddin, Musa Miah, Al-Amin Khan, Ali AlArjani. Goal programming tactic for uncertain multi-objective transportation problem using fuzzy linear membership function. Alexandria Engineering Journal. 2021; 60 (2):2525-2533.
Chicago/Turabian StyleSharif Uddin; Musa Miah; Al-Amin Khan; Ali AlArjani. 2021. "Goal programming tactic for uncertain multi-objective transportation problem using fuzzy linear membership function." Alexandria Engineering Journal 60, no. 2: 2525-2533.
The closed-loop supply chain management (CLSCM) is an attractive research field for the corporate and academic worlds; however, closing the loop is not a simple task. Reverse logistics activities increase management complexities and uncertainties by establishing multi-fold collection and return management processes. Unlike traditional supply chain management, where managers deal with only stochastic demand, in closed-loop supply chain management, they deal with both stochastic demand and returns, which increases the cumulative uncertainty in the system. Firms usually use disposable packaging, and demand uncertainties also increase the negative environmental implications of logistics activities. This study aims to investigate optimal remanufacturing strategy and reusable packaging capacity under stochastic demand and return rate for single and multi-retailer closed-loop supply chain models. The results show that a hybrid policy is an optimal option for both single and multi-retailer cases; however, the rate of remanufacturing increases for multiple-retailers. Furthermore, remanufacturing cost, manufacturing cost, and ordering cost of retailers are the principal drivers of hybrid supply chain management. The results further suggest that supply chain managers should reduce manufacturing and remanufacturing costs because they play a central role in deciding the optimal remanufacturing rate. Increasing the remanufacturing rate increases ordering quantities and reduces setup and ordering costs in the system. Thus the remanufacturing is a relatively inexpensive policy for supply chains with higher setup and ordering costs. Numerical examples, sensitivity analysis, and comparative study show the robustness and validity of the proposed model.
Mehran Ullah; Iqra Asghar; Muhammad Zahid; Muhammad Omair; Ali AlArjani; Biswajit Sarkar. Ramification of remanufacturing in a sustainable three-echelon closed-loop supply chain management for returnable products. Journal of Cleaner Production 2021, 290, 125609 .
AMA StyleMehran Ullah, Iqra Asghar, Muhammad Zahid, Muhammad Omair, Ali AlArjani, Biswajit Sarkar. Ramification of remanufacturing in a sustainable three-echelon closed-loop supply chain management for returnable products. Journal of Cleaner Production. 2021; 290 ():125609.
Chicago/Turabian StyleMehran Ullah; Iqra Asghar; Muhammad Zahid; Muhammad Omair; Ali AlArjani; Biswajit Sarkar. 2021. "Ramification of remanufacturing in a sustainable three-echelon closed-loop supply chain management for returnable products." Journal of Cleaner Production 290, no. : 125609.
Human civilizations are under enormous threats due to the outbreak of novel coronavirus (COVID-19) originated from Wuhan, China. The asymptomatic carriers are the potential spreads of this novel virus. Since, guaranteed antiviral treatments have not been available in the market so far, it is really challenging to fight against this contagious disease. To save the living mankind, it is urgent to know more about how the virus transmits itself from one to another quite rapidly and how we can predict future infections. Scientists and Researchers are working hard in investigating to understand its high infection rate and transmission process. One possible way to know is to use our existing COVID-19 infection data and prepare a useful model to predict the future trend. Mathematical modelling is very useful to understand the basic principle of COVID-19 transmission and provide necessary guidelines for future prediction. Here, we have reviewed 9 distinct commonly used models based on Mathematical implementations for COVID-19 transmission and dig into the deep head to head comparison of each model. Finally, we have discussed interesting key behaviour of each model, relevant upcoming important issues, challenges and future directions.
Sharif Uddin; Taufiq Nasseef; Mufti Mahmud; Ali Alarjani. Mathematical Modelling in Prediction of Novel CoronaVirus (COVID-19) Transmission Dynamics. 2020, 1 .
AMA StyleSharif Uddin, Taufiq Nasseef, Mufti Mahmud, Ali Alarjani. Mathematical Modelling in Prediction of Novel CoronaVirus (COVID-19) Transmission Dynamics. . 2020; ():1.
Chicago/Turabian StyleSharif Uddin; Taufiq Nasseef; Mufti Mahmud; Ali Alarjani. 2020. "Mathematical Modelling in Prediction of Novel CoronaVirus (COVID-19) Transmission Dynamics." , no. : 1.