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.
| Original language | English |
|---|---|
| Pages (from-to) | 443-458 |
| Journal | Production Planning and Control |
| Volume | 11 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - Jul 2000 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- Earliness/tardiness production scheduling and planning (ETPSP)
- Genetic algorithms (GAs)
- Multi-objective (MO)
- Optimization
- Production/inventory management and control (PIMC)
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