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A Bilevel Particle Swarm Optimization Algorithm for Supply Chain Management Problems

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Part of the Studies in Computational Intelligence book series (SCI,volume 482)

Abstract

Nature inspired methods are approaches that are used in various fields and for the solution for a number of problems. In this study, a new bilevel particle swarm optimization algorithm is proposed for solving two well known supply chain management problems, the Vehicle Routing Problem and the Location Routing Problem. The results of the algorithms are compared with the results of algorithms that solve these problems with a single objective function and with a bilevel genetic algorithm. As most of the decisions in Supply Chain Management are taken in different levels, the study presented in this paper has two main goals. The first one is to give to the decision maker the possibility to formulate the supply chain management problems as bilevel or multilevel problems and the second one is to propose an efficient nature inspired algorithm that solves this kind of problems.

Keywords

  • Travel Salesman Problem
  • Vehicle Route Problem
  • Bilevel Programming
  • Route Problem
  • Bilevel Programming Problem

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Marinakis, Y., Marinaki, M. (2013). A Bilevel Particle Swarm Optimization Algorithm for Supply Chain Management Problems. In: Talbi, EG. (eds) Metaheuristics for Bi-level Optimization. Studies in Computational Intelligence, vol 482. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37838-6_3

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  • DOI: https://doi.org/10.1007/978-3-642-37838-6_3

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