Nayera Elgharably
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Nayera Elgharably has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
Ashraf El Damatty
Western University
2 shared publicationsAshraf Nassef
American University in Cairo
2 shared publicationsSaid Easa
Ryerson University
1 shared publication- Said M. Easa
Toronto Metropolitan University
1 shared publication
Latest Publications
- 3 June 2022
- Published by Springer Nature
- p. 513-527
New Hybrid Search Algorithm for the Capacitated Vehicle Routing Problem
- 3 June 2022
- Published by Springer Nature
- p. 513-527
New Hybrid Search Algorithm for the Capacitated Vehicle Routing Problem
- 17 March 2022
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Intelligent Transportation Systems
- Vol. 24 (1) , 1337-1355
Stochastic Multi-Objective Vehicle Routing Model in Green Environment With Customer Satisfaction
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.
- 17 March 2022
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Intelligent Transportation Systems
- Vol. 24 (1) , 1337-1355
Stochastic Multi-Objective Vehicle Routing Model in Green Environment With Customer Satisfaction
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.