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An Ant Colony System for solving the Job Sequencing and Tool Switching Problem

Dehaybe, Henri
(2018)

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Dehaybe_47051200_2018.pdf
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Details

Supervisors
Catanzaro, Daniele
Faculty
Louvain School of Management
Degree label
Master [120] en Ingénieur de gestion
Abstract
In this thesis, we investigate the Job Sequencing and Tool Switching Problem (SSP), a well-known NP-hard problem in operational research arising in flexible manufacturing systems. We present the problem and all its known properties and we review the existing solving procedures in the literature. Then we present a well-known class of metaheuristics, Ant Colony Optimization (ACO), and how it is applied to solve the Travelling Salesman Problem (TSP), a famous problem that shares some properties with the SSP. We hybridize a customized Ant Colony System with a new local search inspired by the 2.5-opt for the TSP. After some tuning, the proposed algorithm becomes strongly competitive with the existing state of the art methods for that problem in the literature.