Journal
SUSTAINABILITY
Volume 11, Issue 2, Pages -Publisher
MDPI
DOI: 10.3390/su11020502
Keywords
integrated process planning and scheduling; genetic algorithm; flexible manufacturing system; chromosome representation
Funding
- Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education [2015R1D1A1A01060391]
- National Research Foundation of Korea [2015R1D1A1A01060391] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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This paper proposes a genetic algorithm (GA) to find the pseudo-optimum of integrated process planning and scheduling (IPPS) problems. IPPS is a combinatorial optimization problem of the NP-complete class that aims to solve both process planning and scheduling simultaneously. The complexity of IPPS is very high because it reflects various flexibilities and constraints under flexible manufacturing environments. To cope with it, existing metaheuristics for IPPS have excluded some flexibilities and constraints from consideration or have built a complex structured algorithm. Particularly, GAs have been forced to construct multiple chromosomes to account for various flexibilities, which complicates algorithm procedures and degrades performance. The proposed new integrated chromosome representation makes it possible to incorporate various flexibilities into a single string. This enables the adaptation of a simple and typical GA procedure and previously developed genetic operators. Experiments on a set of benchmark problems showed that the proposed GA improved makespan by an average of 17% against the recently developed metaheuristics for IPPS in much shorter computation times.
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