A new bi-objective periodic vehicle routing problem with maximization market share in an uncertain competitive environment
- 1. Isfahan University of Technology, Department of Industrial and Systems Engineering (Iran, Islamic Republic of)
- 2. Iran University of Science and Technology, Department of Industrial Engineering (Iran, Islamic Republic of)
Description
This paper presents a new variant of periodic vehicle routing problem in which the reaching time to the customers affects market share. Thus, there is a competition between distributors to achieve more market share by reaching the customers earlier than others; moreover, travel time between each two pairs of customers is uncertain. This situation is called an uncertain competitive environment. For the given problem, a new bi-objective mathematical model including minimization of total traveled time and maximization of the market share is presented. In order to solve this model, a multi-objective particle swarm (MOPSO) and local MOPSO algorithms are applied; and to evaluate the algorithm performance, some samples are generated; and the results of algorithms are compared based on some comparison metrics. The results demonstrate that the proposed LMOPSO algorithm leads to a better performance compared to the MOPSO in most comparison metrics.
Additional details
Identifiers
Publishing Information
- Journal Title
- Computational and Applied Mathematics
- Journal Volume
- 37
- Journal Issue
- 2
- Journal Page Range
- p. 1680-1702
- ISSN
- 0101-8205
INIS
- Country of Publication
- United States
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 50012555
- Subject category
- S97: MATHEMATICAL METHODS AND COMPUTING;
- Descriptors DEI
- ALGORITHMS; COMPARATIVE EVALUATIONS; MATHEMATICAL MODELS; METRICS; MINIMIZATION; PERIODICITY
- Descriptors DEC
- EVALUATION; MATHEMATICAL LOGIC; OPTIMIZATION; VARIATIONS
Optional Information
- Copyright
- Copyright (c) 2018 SBMAC - Sociedade Brasileira de Matem#Latin Small Letter A With Acute#tica Aplicada e Computacional