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Cooperative Ant Colony Algorithm for Flexible Manufacturing Systems

  • Asmaa Kamal
  • Iman Badr
  • Adel Darwish
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 803)

Abstract

An ant colony optimization algorithm that accounts for the special requirements of Flexible Manufacturing Systems (FMS) is presented in this paper. The scheduling problem of FMS is conceived as a classical job shop scheduling problem (JSSP). The objective is to minimize the time taken for all jobs to finish execution (i.e. the makespan). The proposed algorithm accounts for the dynamicity of the FMS environment and automates the schedule update by incorporating newly arrived jobs to the existing schedule. The Ant Colony algorithm is applied to solve different discrete optimization problems by artificial ants, using indirect communication to make all routing decisions by reacting to their dynamically changing environment through cooperation between ants and updating their pheromone trails. The effectiveness of the algorithm proposed in this paper is investigated by examining numerical results, and the computational experiments have been executed based on the JSSP data benchmarks.

Keywords

Flexible manufacturing systems Job shop schedule problem Re-scheduling Ant colony system 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Mathematics Department, Faculty of ScienceHelwan UniversityHelwanEgypt

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