TERMHIGEN – A hybrid metaheuristic technique for solving large-scale vehicle routing problem with time windows

Fagbola, Temitayo Matthew; Thakur, Surendra Colin

Abstract

Vehicle Routing Problem with Time Windows (VRPTW) involves traversing a coordinated set of vehicular paths such that a set of customers is visited once within a given time-stamped boundary. VRPTW poses a great challenge to logistics distribution and supply chain management systems, due to its characterized stochastic and NP-hard combinatorial properties, which requires that its corresponding optimal path planning and vehicle scheduling solutions be both highly efficient and cost effective even as customers’ demands change dynamically. In this paper, a new hybrid metaheuristic scheme, tagged TERMHIGEN, based on the characteristics of the Termite-Hill algorithm and a modified Genetic Algorithm, with its associated adaptive self-learning and tuning schemes, based on is developed and applied to solving a prototype VRPTW specifically with the objective of minimizing overall logistic distribution cost. TERMHIGEN was tested using Solomon’s 56 VRPTW instances containing 100 customers. The performance evaluation results of the algorithms reveal that TERMHIGEN produced more optimal and efficient outputs for some problem instances than those produced by some baseline metaheuristic techniques in terms of computational time efficiency and distance travelled.

Citation

Fagbola, T. M., & Thakur, S. C. (2019). TERMHIGEN – A hybrid metaheuristic technique for solving large-scale vehicle routing problem with time windows. International Journal of Engineering Research & Technology, 12(2), 180-195

• Journal Article Type: Article
• Publication Date: Jan 1, 2019
• Deposit Date: Jan 28, 2024
• Journal: International Journal of Engineering Research and Technology
• Peer Reviewed: Peer Reviewed
• Volume: 12
• Issue: 2
• Pages: 180-195
• Public URL: https://hull-repository.worktribe.com/output/4161545
• Publisher URL: http://www.irphouse.com/ijert19/ijertv12n2_07.pdf