A Hybrid Approach Based on LP Metric Method and Genetic Algorithm for the Vehicle-Routing Problem with Time Windows, Driver-Specific Times, and Vehicles-Specific Capacities

• Published in: International journal of operations research and information systems Vol. 9; no. 4; pp. 51 - 67
• Main Authors: Asadi-Gangraj, Ebrahim, Nayeri, Sina
• Format: Journal Article
• Language: English
• Published: Hershey IGI Global 01.10.2018
• Subjects: Algorithms; Automobile drivers; Computing time; Cost control; Customer satisfaction; Customer services; Exact solutions; Genetic algorithms; Genetic research; Information systems; Integer programming; Methods; Mixed integer; Operations research; Roads & highways; Transportation planning; Vehicle routing; Vehicles; Windows (intervals); Workforce
• ISSN: 1947-9328; 1947-9336
• DOI: 10.4018/IJORIS.2018100104

Due to increasing population, increasing number of vehicles as well as environmental pollution, planning vehicles efficiently one of important problems nowadays. This article proposes a Multi-Objective Mixed Integer Programming (MOMIP) model for the vehicle-routing problem with time windows, driver-specific times and vehicles-specific capacities (VRPTDV), a variant of the classical VRPT that uses driver-specific travel and service times and vehicles-specific capacity to model the familiarity of the different drivers with the customers to visit. The first objective function aims to minimize traveled distance and the second objective function minimizing working duration. Since the problem is NP-hard, optimal solution for the instances of realistic size cannot be obtained within a reasonable amount of computational time using exact solution approaches. Hence, the hybrid approach based on LP metric method and genetic algorithm is proposed to solve the given problem.