TY - JOUR ID - 70834 TI - Integrated Process Planning and Active Scheduling in a Supply Chain-A Learnable Architecture Approach JO - Interdisciplinary Journal of Management Studies (Formerly known as Iranian Journal of Management Studies) JA - IJMS LA - en SN - AU - Moradi, Esmaeel AU - Ayough, Ashkan AU - Zandieh, Mostafa AD - School of Industrial Engineering and Management, Oklahoma State University, Stillwater, USA AD - Department of Industrial Management, Management and Accounting Faculty, Shahid Beheshti University, Tehran, Iran Y1 - 2019 PY - 2019 VL - 12 IS - 2 SP - 307 EP - 333 KW - Supply Chain Management KW - Process planning KW - Scheduling KW - Transformation matrix KW - Evolutionary search DO - 10.22059/ijms.2019.255363.673086 N2 - 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. UR - https://ijms.ut.ac.ir/article_70834.html L1 - https://ijms.ut.ac.ir/article_70834_58ee99de1ae3848dd3f2aeb08469ab44.pdf ER -