Integrated Process Planning and Active Scheduling in a Supply Chain-A Learnable Architecture Approach
Publish place: Iranian Journal of Management Studies، Vol: 12، Issue: 2
Publish Year: 1398
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_JIJMS-12-2_007
تاریخ نمایه سازی: 6 شهریور 1402
Abstract:
Through the lens of supply chain management, integrating process planning decisions and scheduling plans becomes an issue of great challenge and importance. Dealing with the problem paves the way to devising operation schedules with minimum makespan; considering the flexible process sequences, it can be viewed as a fundamental tool for achieving the scheme, too. To deal with this integration, the modeling approach to problem with MIP structure is common in the literature. These models take precedence constraints into consideration to select machines and to determine sequences. In order to obtain viable sequences, we employed a proposed transformation matrix (TM). We also took advantage of an evolutionary search, called Learnable genetic Architecture (LEGA). Based on LEGA, we developed an integrated process planning and scheduling learnable genetic algorithm (IPPSLEGA). Our approach was evaluated with problems with various sizes. The experimental results show that our proposed architecture outperforms prior approaches, or it performs, at least, as efficiently as they do.
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Authors
اسماعیل مرادی
School of Industrial Engineering and Management, Oklahoma State University, Stillwater, USA
اشکان عیوق
Department of Industrial Management, Management and Accounting Faculty, Shahid Beheshti University, Tehran, Iran
مصطفی زندیه
Department of Industrial Management, Management and Accounting Faculty, Shahid Beheshti University, Tehran, Iran
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