A genetic algorithm for multi-level, multi-machine lot sizing and scheduling

This contribution introduces a mixed-integer programming formulation for the multi-level, multi-machine proportional lot sizing and scheduling problem. It also presents a genetic algorithm to solve that problem. The efficiency of that algorithm is due to an encoding of solutions which uses a two-dim...

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Veröffentlicht in:	Computers & operations research Jg. 26; H. 8; S. 829 - 848
1. Verfasser:	Kimms, A.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Oxford Elsevier Ltd 01.07.1999 Elsevier Science Pergamon Press Inc
Schlagworte:	Algorithms Applied sciences Exact sciences and technology Genetic algorithms Integer programming Manufacturing resource planning Multi-level lot sizing Operational research and scientific management Operational research. Management science Operations research PLSP Scheduling Scheduling, sequencing Studies Scheduling PLSP Multi-level lot sizing Genetic algorithms Manufacturing resource planning Mixed integer programming Lot sizing Genetic algorithm Multilevel system
ISSN:	0305-0548, 1873-765X, 0305-0548
Online-Zugang:	Volltext
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