Job Shop Scheduling: A Case Study

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During the recent past period, academic researchers and practitioners devoted their efforts for improving the scheduling process and developing an effective approach. They were seeking to optimize scheduling problems through exploration and exploitation the solution space. The first section in this chapter presents two different optimization approaches that are able to solve and optimize job shop scheduling problem. The first type of optimization approaches is based on exact algorithms and they are usually used for simple and small size problem. Another type of approaches is based on more sophisticated algorithms that can be applied to more complex and larger problems. These approaches are denoted as approximate algorithms where the solutions may be optimal or near-optimal. Approximate algorithms can be classified into heuristic and meta-heuristic methods. The main purpose of this chapter is to present a comprehensive survey of different approaches available for solving the job-shop scheduling problem. It will be important also to identify the trend of research and the gaps that require further research in the second section of this chapter Jain and Meeran [12].

3.2 Exact Methods

Over the last years, various types of exact methods were proposed for developing the job shop scheduling problem (JSSP). Exact methods are considered simple approaches. They do guarantee optimal solutions as long as problems are small. Most of the JSSPs can be formulated as linear programming,

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