Seeking Simulation-based Optimization of Job shop Scheduling in Small and Medium Enterprises to Minimize the Cost of Tardiness and Earliness of Activities

Document Type : Research Paper


1 Assistant Prof. in New Business Group, Faculty of Entrepreneurship, Tehran University, Tehran, Iran

2 Ph.D Candidate of Industrial Engineering, Faculty of Industrial Engineering, Tehran University, Tehran, Iran


Determining the optimal sequence of jobs in job shop scheduling for small and medium enterprises, affect the machine productivity, earliness and tardiness costs of delivery. The deterministic variant of the problem is well-known to be NP-Hard. If random elements are introduced into the problem, the level of complexity goes higher. Hence, many priority rules have been developed to tackle stochastic job shop scheduling problem. However, to devise a better solution approach, simulation-optimization approach might be used. In this study, a mathematical model was developed for job shop scheduling with random process times and possible machine breakdowns. Then, a simulation-optimization model was applied to choose among a list of priority rules using Rockwell Arena 14. Finally, a numerical example was used to evaluate the quality of the model. Results showed that the rule Longest Processing Time (LPT) yields the lowest total earliness and tardiness costs. However, the total costs of the following rules are also acceptable: First in First out (FIFO), Last in First out (LIFO), Earliest Due Date (EDD) and Slack time (Slack).


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