An improved hybrid firefly algorithm for capacitated vehicle routing problem

The traditional distribution planning problem in a supply chain has often been studied mainly with a focus on economic benefits. The growing concern about the effects of anthropogenic pollutions has forced researchers and supply chain practitioners to address the socio-environmental concerns. This research study focuses on incorporating the environmental impact on route design problem. In this work, the aim is to integrate both the objectives, namely economic cost and emission cost reduction for a capacitated multi-depot green vehicle routing problem. The proposed models are a significant contribution to the field of research in green vehicle routing problem at the operational level. The formulated integer linear programming model is solved for a set of small scale instances using LINGO solver. A computationally efficient Ant Colony Optimization (ACO) based meta-heuristic is developed for solving both small scale and large scale problem instances in reasonable amount of time. For solving large scale instances, the performance of the proposed ACO based meta-heuristic is improved by integrating it with a variable neighbourhood search.

Design and development of a hybrid ant colony-variable neighbourhood search algorithm for a multi-depot green vehicle routing problem

Solving capacitated vehicle routing problem using cooperative firefly algorithm

With the rapid growth of perishable food e-commerce businesses, there is a definite need for logistics services providers to manage parcel shipments with multi-temperature requirements. E-commerce ...

Integrating Internet of Things and multi-temperature delivery planning for perishable food E-commerce logistics: a model and application

The capacitated vehicle routing problem (CVRP) is one of the commonly studied issues today. It belongs to the class of NP-hard problems and has a high time complexity. Therefore, the solution of the CVRP was focused in this study. An improved simulated annealing algorithm with crossover operator, called ISA-CO, was proposed. A population based simulated annealing algorithm was used in the proposed algorithm. The solutions in the population were developed through the local search operators, including swap, scramble, insertion, and reversion. The improved 2-opt algorithm was used to develop the routes making up the solution. The partially mapped crossover (PMX) and the order crossover (OX) operators were applied to the solutions in the population to accelerate the convergence. A mix selection method was used to ensure the balance between exploitation and exploration. The ISA-CO was tested on 91 well-known benchmark instances. The results indicated that the method has a better performance compared to other state-of-the-art methods on many instances.

Marwa Amous

Papers

A variable neighborhood search algorithm for the capacitated vehicle routing problem