Dr. Said Easa
Ryerson University
+1
'%3e%3cpath%20d='M22.1642%2019.0924C21.7317%2018.068%2021.1041%2017.1375%2020.3163%2016.3527C19.5309%2015.5656%2018.6006%2014.9381%2017.5766%2014.5048C17.5674%2014.5002%2017.5582%2014.4979%2017.5491%2014.4933C18.9774%2013.4616%2019.9059%2011.7811%2019.9059%209.88504C19.9059%206.74408%2017.3611%204.19922%2014.2201%204.19922C11.0792%204.19922%208.53429%206.74408%208.53429%209.88504C8.53429%2011.7811%209.46282%2013.4616%2010.8912%2014.4956C10.882%2014.5002%2010.8728%2014.5025%2010.8636%2014.5071C9.83652%2014.9404%208.91487%2015.5617%208.1239%2016.355C7.33685%2017.1404%206.70933%2018.0707%206.276%2019.0947C5.85031%2020.0972%205.62072%2021.172%205.59967%2022.2609C5.59905%2022.2853%205.60335%2022.3097%205.61229%2022.3325C5.62123%2022.3553%205.63465%2022.376%205.65174%2022.3935C5.66883%2022.4111%205.68926%2022.425%205.71182%2022.4345C5.73437%2022.444%205.7586%2022.4489%205.78308%2022.4489H7.15868C7.25956%2022.4489%207.3398%2022.3686%207.3421%2022.2701C7.38795%2020.5001%208.09868%2018.8425%209.35506%2017.5861C10.655%2016.2862%2012.3814%2015.5709%2014.2201%2015.5709C16.0588%2015.5709%2017.7852%2016.2862%2019.0852%2017.5861C20.3415%2018.8425%2021.0523%2020.5001%2021.0981%2022.2701C21.1004%2022.3709%2021.1807%2022.4489%2021.2815%2022.4489H22.6571C22.6816%2022.4489%2022.7058%2022.444%2022.7284%2022.4345C22.751%2022.425%2022.7714%2022.4111%2022.7885%2022.3935C22.8056%2022.376%2022.819%2022.3553%2022.8279%2022.3325C22.8369%2022.3097%2022.8412%2022.2853%2022.8406%2022.2609C22.8176%2021.165%2022.5907%2020.0989%2022.1642%2019.0924ZM14.2201%2013.8284C13.1678%2013.8284%2012.1773%2013.418%2011.4322%2012.6729C10.6871%2011.9278%2010.2767%2010.9374%2010.2767%209.88504C10.2767%208.83271%2010.6871%207.84227%2011.4322%207.09715C12.1773%206.35204%2013.1678%205.94165%2014.2201%205.94165C15.2724%205.94165%2016.2629%206.35204%2017.008%207.09715C17.7531%207.84227%2018.1635%208.83271%2018.1635%209.88504C18.1635%2010.9374%2017.7531%2011.9278%2017.008%2012.6729C16.2629%2013.418%2015.2724%2013.8284%2014.2201%2013.8284Z'%20fill='%238590A2'/%3e%3c/g%3e%3c/svg%3e)
Co-authors
Following
Followers
Research Focus & Metrics
Explore full metrics on Scilit
Academic Career Length
31Years (1996-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications1 August 2008 in Journal of Construction Engineering and Management
Journal Article
Said EasaKHKhandaker Hossain
Khandaker HossainLayout of temporary construction facilities (objects) is an important activity during the planning process of construction projects. The construction area layout is a complex problem whose solution requires the use of analytical models. Existing popular models employ genetic algorithms that have proven to be useful tools in generating near optimal site layouts. This paper presents an alternative approach based on mathematical optimization that offers several important features and generates a global optimal solution. The construction area consists of an unavailable area that includes existing facilities (sites) and available area in which the objects can be located. The available area is divided into regions that are formulated using binary variables. The locations of the objects are determined by optimizing an objective function subject to a variety of physical and functional constraints. The objective function minimizes the total weighted distance between the objects and the sites as well as among the o...
17 March 2022 in IEEE Transactions on Intelligent Transportation Systems
Journal Article
NENayera Elgharably
Nayera ElgharablySaid EasaANAshraf Nassef
Ashraf Nassef
ADAshraf El Damatty
Ashraf El Damatty
The Vehicle Routing Problem (VRP) is one of the most studied combinatorial optimization problems in operations research that are classified as NP-hard. Introducing uncertainty to the problem increases the complexity of solving such problems. Sources of uncertainty in a VRP can be travel times, service times, and unpredictable demands of customers. Ignoring these sources may lead to inaccurate modeling of the VRP. Moreover, the area of green logistics and the environmental issues associated received significant attention. This paper aims to study the stochastic multi-objective Vehicle Routing Problem in a green environment. The stochastic Green VRP (GVRP) presented deals with three objectives simultaneously that consider economic, environmental, and social aspects. First, a new hybrid search algorithm to solve the VRP is presented and validated. The algorithm is then employed to solve the stochastic multi-objective GVRP. Pareto fronts were obtained, and trade-offs between the three objectives are presented. Furthermore, an analysis of the effect of customers' time window relaxation is presented.
6 March 2023 in Accident Analysis & Prevention
Journal Article
NGNinad Gore
Ninad GoreRCRitvik Chauhan
Ritvik ChauhanSaid EasaSAShriniwas Arkatkar
Shriniwas Arkatkar
Journal Article
AAAbayomi Afolayan
Abayomi AfolayanSaid EasaOAOladapo Abiola
Oladapo AbiolaFAFunmilayo M. Alayaki
Funmilayo M. AlayakiOFOlusegun Folorunso
Olusegun FolorunsoThis study identified high-risk locations (hotspots) using geographic information systems (GIS) and spatial analysis. Five years of accident data (2013–2017) for the Lokoja-Abuja-Kaduna highway in Nigeria were used. The accident concentration analysis was conducted using the mean center analysis and Kernel density estimation method. These locations were further verified using Moran’s I statistics (spatial autocorrelation) to determine their clustering with statistical significance. Fishnet polygon and network spatial weight matrix approaches of the Getis–Ord Gi* statistic were used in the hotspot analysis. Hotspots exist for 2013, 2014, and 2017 with a significance level between 95–99%. However, hotspots for 2015 and 2016 have a low significance level and the pattern is random. The spatial autocorrelation analysis of the overall accident locations and the Moran’s I statistic showed that the distribution of the accidents on the study route is random. Thus, preventive measures for hotspot locations should be based on a yearly hotspot analysis. The average daily traffic values of 31,270 and 16,303 were obtained for the northbound and southbound directions of the Abaji–Abuja section. The results show that hotspot locations with high confidence levels are at points where there are geometric features.
1 December 2016 in Journal of Transportation Engineering
Journal Article
Based on field data collected at nine roundabouts in Gold Coast, Australia, this paper evaluates the performance of the capacity estimation for single-lane roundabouts using analytical models [including the highway capacity manual (HCM) 2000 model, the German Highway Capacity Manual (GHCM) model, the signalized and unsignalized intersection design and research aid (SIDRA) model and a new roundabout capacity (NRC) model] and an empirical model (the HCM 2010 model). First, this study calibrates critical gaps, follow-up times, and conflicting flows. Compared with the capacities measured in the field, the authors carry out a study to analyze the accuracy of the HCM, GHCM, SIDRA, and NRC models. The results show that the five models underestimate capacity but the NRC model produces a smaller range of relative error (−1.07 to −5.74%) and root-mean-square deviation (47.68) than the HCM 2010 (−4.62 to −16.14% and 105.00, respectively), HCM 2000 (−5.76 to −17.21% and 115.29, respectively), GHCM (−8.95 to −...
1 June 2009 in Journal of Irrigation and Drainage Engineering
Journal Article
Said EasaA channel cross section with parabolic sides and horizontal bottom has been recently published and proved to be more economical (provide lesser construction cost per unit length) than the trapezoidal cross section. This paper presents a new and improved cross section with two-segment parabolic sides and horizontal bottom. Each side of the cross section consists of two parabolic segments smoothly connected. Closed-form relationships for the cross-sectional area and perimeter are developed. For specific parameter conditions, the new cross section produces most of the common cross sections, including the parabolic sides—horizontal bottom and trapezoidal cross sections, as well as new cross-sectional shapes. It provides an additional degree of freedom in determining the optimal cross-sectional design. A spreadsheet-based optimization model for the new cross section that minimizes the total construction cost (excavation and composite linings) is developed. The constraints of the model include channel discharge...
About Me
Prof. Dr. Said M. Easa is a Professor at the Department of
Civil Engineering, Toronto Metropolitan University, Toronto, Canada. Before
joining Toronto Metropolitan University, he worked as an Associate Professor
and then Professor at Lakehead University from 1982 to 2000. At Toronto
Metropolitan University, he also served as the Chair of the Department of Civil
Engineering during 2000–2006 and the Director of Quality Assurance, FEAS during
2010–2013. He obtained his B.Sc. in Civil Engineering from Cairo University in
1972, his M.Eng. in Transportation from McMaster University in 1976, and his
Ph.D. in Transportation from the University of California at Berkeley in 1982.
His research interests include geometric design and road safety, intelligent
transportation systems, and traffic operations and management. He is a member
of several scientific societies, such as the PEMAC Asset Management Association
of Canada, the Canadian Society for Civil Engineering (CSCE), the American
Society of Civil Engineers (ASCE), the International Association of Advanced
Materials (IAAM), and the Professional Engineers Ontario. Prof. Dr. Easa has
received many awards, including the Best Presentation Award at the
International Conference on Psychology in 2023, the Best Paper Award of the
Journal of Intelligent and Connected Vehicles in 2023, the IAAM Fellow Award in
2020, the IAAM Lecture Award in 2020, and the IAAM Medal in 2018.