Abstract

: Received 1 Feb 2010 Received in revised form 10 June 2010 Accepted 20 June 2010 Available online 23 June 2010 Job shop scheduling (JSS) problem has been one of the most interesting research issues in the literature during the recent years. JSS problem has been studied in different forms of deterministic, fuzzy, and stochastic at different depths. The idea of robust optimization (ROP), on the other hand, has earned a particular value to become a popular subject of the breakthrough for problem solving affairs amongst the researchers. Based on the emerged opportunity for illustrating a new area of search, a robust JSS problem is proposed as a challenge to this boundary of knowledge. The proposed method is capable of handling the perturbation which exists amongst the processing times. In fact, in many real world job scheduling problems, a small change in the processing times, not only causes a non-optimal solution, but also the infeasibility of the final solution may also occur. The proposed robust method could guarantee that, a small deviation of the processing times does not affect the feasibility. The implementation of the proposed method is illustrated using some numerical examples and the outcomes of the investigation are discussed

Highlights

  • The job shop-scheduling (JSS) problem normally deals with manufacturing industry where there are many practical applications on this sector

  • We have presented a robust JSS problem which has the capability of handling the perturbation which exists amongst almost all input parameters

  • For many real world job scheduling problems, a small change in input parameters may lead us to some final solutions which are neither feasible nor optimal

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Summary

Introduction

The job shop-scheduling (JSS) problem normally deals with manufacturing industry where there are many practical applications on this sector. 2. Robust Job Shop Problem As we explained, the perturbation is normally occurs in JSS problem, especially in the processing times of jobs in each machine. One can assume that the operation of job 1 in machine 1 is subjected to perturbation and the processing time is increased by one.

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