Abstract
Batch scheduling is a well-known topic that has been studied widely with various objectives, methods, and circumstances. Unfortunately, batch scheduling in a collaborative flow shop system is still unexplored. All studies about batch scheduling that are found were in a single flow shop system where all arriving jobs come from single door. In a collaborative flow shop system, every flow shop handles its own customers although joint production among flow shops to improve efficiency is possible. This work aims to develop a novel batch scheduling model for a collaborative multi-product flow shop system. Its objective is to minimize make-span and total production cost. This model is developed by using non-dominated sorting genetic algorithm (NSGA II) which is proven in many multi objective optimization models. This model is then compared with the non-collaborative models which use NSGA II and adjacent pairwise interchange algorithm. Due to the simulation result, the proposed model performs better than the existing models in minimizing the make-span and total production cost. The make-span of the proposed model is 10 to 17 percent lower than the existing non-collaborative models. The total production cost of the proposed model is 0.3 to 3.5 percent lower than the existing non-collaborative models.
Highlights
Batch scheduling is a well-known topic in supply chain management, especially in production process
Based on the simulation result, in general, the collaborative approach is better than the non-collaborative one. it is shown that the collaborative model outperforms the non-collaborative models in make-span and is slightly better in total production cost
This work shows that the proposed collaborative batch scheduling model meets the research objective in minimizing the make-span and the total production cost
Summary
Batch scheduling is a well-known topic in supply chain management, especially in production process. Batch scheduling studies were studied in flow shop system. Production is divided into several stages [12]. These stages can be production, assembling, or inspection. The flow shop can be permutation or nonpermutation. In the permutation flow shop, once these jobs are sequenced, this sequence will be fixed for all stages [13]. In the non-permutation flow shop, the jobs sequence among stages may be different [14]. In the batch scheduling in a flow shop system, the jobs are batched first before sequenced
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