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Scheduling and planning problem in manufacturing systems with multiobjective genetic algorithm

Research output: Journal Publications and ReviewsRGC 62 - Review of books or of software (or similar publications/items)peer-review

Abstract

In this paper an extensive earliness/tardiness production scheduling and planning(ETPSP) model with lot-size consideration and capacity balance is proposed. An innovative approach using multiobjective genetic algorithm (MOGA) is designed as its solutions. The presented MOGA approach can even deal with ETPSP problem which consists of highly complicated and nonlinear functions for the measure performance. The effectiveness of this approach is demonstrated by simulation results as well as the comparisons with other techniques.
Original languageEnglish
Pages (from-to)274-279
JournalIECON Proceedings (Industrial Electronics Conference)
Volume1
Publication statusPublished - 1998
EventProceedings of the 1998 24th Annual Conference of the IEEE Industrial Electronics Society, IECON. Part 4 (of 4) - Aachen, Ger
Duration: 31 Aug 19984 Sept 1998

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

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