EBBO: an enhanced biogeography-based optimization algorithm for a vehicle routing problem with heterogeneous fleet, mixed backhauls, and time windows

• Published in: International journal of advanced manufacturing technology Vol. 77; no. 9-12; pp. 1711 - 1725
• Main Authors: Berghida, Meryem, Boukra, Abdelmadjid
• Format: Journal Article
• Language: English
• Published: London Springer London 01.04.2015; Springer Nature B.V
• Subjects: Algorithms; Ant colony optimization; Biogeography; CAE) and Design; Computer simulation; Computer-Aided Engineering (CAD; Customers; Engineering; Industrial and Production Engineering; Mechanical Engineering; Media Management; Optimization algorithms; Original Article; Route planning; Routing; Simulated annealing; Vehicle routing; Windows (intervals); Time windows; Biogeography based optimization; Pickup and delivery; Vehicle routing problem; Simulated annealing
• ISSN: 0268-3768; 1433-3015
• DOI: 10.1007/s00170-014-6512-1

This paper presents a new enhanced biogeography-based optimization algorithm (EBBO) for a complex variant of vehicle routing problem (VRP) called HVRPMBTW (vehicle routing problem with heterogeneous fleet, mixed backhauls, and time windows). This variant is characterized by a limited number of vehicles with various capacities and costs. The vehicles serves two types of customers: linehaul customers and backhaul customers. Each customer must be visited in a specific interval of time. We propose to improve and to adapt the biogeography-based optimization (BBO) approach to the problem by integrating simulated annealing algorithm to enhance solution quality, at each iteration. This new approach was tested on benchmarks and produces very satisfactory results compared to other approaches, PSO and ACO [ 1 ].