Authors:
Tao-Shen Li
1
and
Jing-Li Wu
2
Affiliations:
1
School of Computer, Electronics and Information, Guangxi University, China
;
2
School of Mathematics and Computer, Guangxi Normal University, China
Keyword(s):
Vehicle routing problem with time windows; Genetic algorithm; Crossover operator; Routing; heuristics.
Related
Ontology
Subjects/Areas/Topics:
Business and Social Applications
;
Communication and Software Infrastructure
;
e-Business
;
e-Commerce and e-Business: B2B and B2C
;
e-Marketing and Consumer Behaviour
;
Enterprise Information Systems
;
Global Communication Information Systems and Services
;
Information and Systems Security
;
Telecommunications
Abstract:
Many practical transport logistics and distribution problems can be formulated as the vehicle routing problem with time windows (VRPTM). The objective is to design an optimal set of routes that services all customers and satisfies the given constraints, especially the time window constraints. The complexity of the VRPTW requires heuristic solution strategies for most real-life instances. However, the VRPTM is a combination optimization problem and is a NP-complete problem, so we can’t get satisfying results when we use exact approaches and normal heuristic ones. In this paper, an improved genetic algorithm to solve the VRPTM problem is developed, which use an improved Route Crossover operator (RC’) and can meet the needs for solving VRPTM problem. Computational experiments show that the GA based on RC’ can obtain a general optimality for all evaluated indexes on the premise of satisfying every customer’s demand and its performance is superior to the GA based on PMX or RC.