Decision Support System for Solving Multi-Objective Routing Problem
This paper presented a technique to solve one of the transportation problems that faces us in real life which is the Bus Scheduling Problem. Most of the countries using buses in schools, companies and traveling offices as an example to transfer multiple passengers from many places to specific place and vice versa. This transferring process can cost time and money, so we build a decision support system that can solve this problem. In this paper, a genetic algorithm with the shortest path technique is used to generate a competitive solution to other well-known techniques. It also presents a comparison between our solution and other solutions for this problem.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1123807Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1195
 Marti, “Heuristic Solutions to the Problem of Routing School Buses with Multiple Objectives”, 2000.
 Spada, “Decision-aid Methodology for the School Bus Routing and Scheduling Problem”, 2003.
 Kidwai, "A Genetic Algorithm based Bus Scheduling Model for Transit Network", 2005.
 Dias, "A Genetic Algorithm for the Bus Driver Scheduling Problem", 2001.
 Schittekat, "A metaheuristic for solving large instances of the School Bus Routing Problem", 2006.
 Schittekat, "An efficient metaheuristic for the School Bus Routing Problem", 2012.
 James, "Decision Support System for Vehicle Scheduling in Uganda: A Case Study of Gateway Bus Company", 2008.
 Bielli, "Genetic Algorithms in bus network optimization", 2002.
 Lourenco, "Metaheuristics for The Bus Driver Scheduling Problem", 2001.
 Suhl, "Progress in solving large scale multi-depot multi-vehicle-type bus scheduling problems with integer programming", 2008.
 Nayati, "School Bus Routing and scheduling using GIS", 2008.
 Shen, "Tabu Search for Bus & Train Driver Scheduling with Time Windows", 2001
 Torrance"Vehicle and Driver Scheduling for Public Transit", 2009.