Flow-shop systems with machine bypass represent production approaches currently widely adopted in several industrial fields (i.e. electronic and belt industries). As a consequence of differences in the manufacturing process, in those systems, jobs are not forced to stop by each machine. Moreover, if a job does not need processing on a machine, it can skip that machine and the very job eventually residing there. In this paper, a new heuristic for solving the flow-shop scheduling problem with machine bypass is presented. The algorithm is able to manage several scheduling performance measures, finding a set ofnon-dominated solutions representing the Pareto front. The heuristic integrates a priority rule and a local search procedure with a Multi Attribute Decision Making (MADM) technique in such a way as to drive the search direction towards good trade-off solutions. To show the effectiveness of the proposed approach some computational results are presented.
A HEURISTIC FOR THE FLOW-SHOP SCHEDULING WITH MACHINE BYPASS / Gamberini, Rita; Grassi, Andrea; Mora, C.. - ELETTRONICO. - (2005), pp. ---. (Intervento presentato al convegno 18th International Conference on Production Research tenutosi a Fisciano (SA), Italy nel 31st July - 4th August).
A HEURISTIC FOR THE FLOW-SHOP SCHEDULING WITH MACHINE BYPASS
GAMBERINI, Rita;GRASSI, Andrea;
2005
Abstract
Flow-shop systems with machine bypass represent production approaches currently widely adopted in several industrial fields (i.e. electronic and belt industries). As a consequence of differences in the manufacturing process, in those systems, jobs are not forced to stop by each machine. Moreover, if a job does not need processing on a machine, it can skip that machine and the very job eventually residing there. In this paper, a new heuristic for solving the flow-shop scheduling problem with machine bypass is presented. The algorithm is able to manage several scheduling performance measures, finding a set ofnon-dominated solutions representing the Pareto front. The heuristic integrates a priority rule and a local search procedure with a Multi Attribute Decision Making (MADM) technique in such a way as to drive the search direction towards good trade-off solutions. To show the effectiveness of the proposed approach some computational results are presented.
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