Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/26383
Title: Genetic algorithm to production planning and scheduling problems for manufacturing systems
Authors: Li, Y
Man, KF
Tang, KS
Kwong, S
Ip, WH 
Keywords: Earliness/tardiness production scheduling and planning (ETPSP)
Genetic algorithms (GAs)
Multi-objective (MO)
Optimization
Production/inventory management and control (PIMC)
Issue Date: 2000
Publisher: Taylor & Francis
Source: Production planning and control, 2000, v. 11, no. 5, p. 443-458 How to cite?
Journal: Production planning and control 
Abstract: Fundamental and extended multi-objective (MO) models are designed to address earliness/tardiness production scheduling planning (ETPSP) problems with multi-process capacity balance, multi-product production and lot-size consideration. A canonical genetic algorithm (GA) approach and a prospective multi-objective GA (MOGA) approach are proposed as solutions for different practical problems. Simulation results as well as comparisons with other techniques demonstrate the effectiveness of the MOGA approach, which is a noted improvement to any of the existing techniques, and also in practice provides a new trend of integrating manufacturing resource planning (MRPII) with just-in-time (JIT) in the production planning procedure.
URI: http://hdl.handle.net/10397/26383
ISSN: 0953-7287
EISSN: 1366-5871
DOI: 10.1080/09537280050051942
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