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Sequencing in a Non-permutation Flowshop with Constrained Buffers: Applicability of Genetic Algorithm versus Constraint Logic Programming

Salhi, Said, Farber, Gerrit, Coves, Anna M. (2006) Sequencing in a Non-permutation Flowshop with Constrained Buffers: Applicability of Genetic Algorithm versus Constraint Logic Programming. LNCS, 4818 . pp. 536-544. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:25483)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.

Abstract

Mixed model production lines consider more than one model being processed on the same production line in an arbitrary sequence. Nevertheless, the majority of publications in this area are limited to solutions which determine the job sequence before the jobs enter the line and maintains it without interchanging jobs until the end of the production line, which is known as permutation flowshop. This paper considers a non-permutation flowshop. Resequencing is permitted where stations have access to intermediate or centralized resequencing buffers. The access to the buffers is restricted by the number of available buffer places and the physical size of the products. Two conceptually different approaches are presented in order to solve the problem. The fi rst approach is a hybrid approach, using Constraint Logic Programming (CLP), whereas the second one is a Genetic Algorithm (GA). Improvements that come with the introduction of constrained resequencing buffers are highlighted. Characteristics such as the difference between the intermediate and the centralized case are analyzed,

and the special case of semi dynamic demand is studied. Finally, recommendations are presented for the applicability of the hybrid approach, using CLP, versus the Genetic Algorithm.

Item Type: Article
Uncontrolled keywords: Non-permutation fl owshop; Constrained buffers; Mixed model assembly line Genetic Algorithm; Constraint Logic Programming.
Subjects: H Social Sciences > H Social Sciences (General)
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Said Salhi
Date Deposited: 08 Sep 2010 12:43 UTC
Last Modified: 19 Sep 2023 15:04 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/25483 (The current URI for this page, for reference purposes)

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