A Novel Heuristic Rule for Job Shop Scheduling

A Novel Heuristic Rule for Job Shop Scheduling

Shahid Maqsood (School of Engineering, Design & Technology, Richmond Road, University of Bradford, Bradford, West Yorkshire, UK, & Department of Industrial Engineering, NWFP University of Engineering and Technology, Peshawar, Pakistan), M. Khurshid Khan (School of Engineering, Design & Technology, Richmond Road, University of Bradford, Bradford, West Yorkshire, UK), Alastair Wood (School of Engineering, Design & Technology, Richmond Road, University of Bradford, Bradford, West Yorkshire, UK) and I. Hussain (II. Department of Industrial Engineering, KPK University of Engineering and Technology, Peshawar, Pakistan)
DOI: 10.4018/jcrmm.2013010103
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Abstract

Scheduling systems based on traditional heuristic rules, which deal with the complexities of manufacturing systems, have been used by researchers for the past six decades. These heuristics rules prioritise all jobs that are waiting to be processed on a resource. In this paper, a novel Index Based Heuristic (IBH) solution for the Job Shop Scheduling Problem (JSSP) is presented with the objective of minimising the overall Makespan (Cmax). The JSSP is still a challenge to researchers and is far from being completely solved due to its combinatorial nature. JSSP suits the challenges of current manufacturing environments. The proposed IBH calculates the indices of candidate jobs and assigns the job with the lower index value to the available machine. To minimise the gap between jobs, a swap technique is introduced. The swap technique takes candidate jobs for a machine and swaps them without violating the precedence constraint. Several benchmark problems are solved from the literature to test the validity and effectiveness of the proposed heuristic. The results show that the proposed IBH based algorithm outperforms the traditional heuristics and is a valid methodology for JSSP optimization.
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2. Job Shop Scheduling Problem (Jssp)

An efficient scheduling system is an essential part of any manufacturing environment and depends on the scheduling scenario (Janiak & Janiak, 2011; Maqsood, et al., 2011; Noor & Khan, 2007). In the literature various researchers (Blazewicz, Ecker, & Trystram, 2005; Blazewicz, Ecker, Pesch, Schmidt, & Weglarz, 1996; Jain & Meeran, 1998; Morshed, 2006; Noor, 2007; Zhang & Wu, 2010) have discussed mathematical models with the objective function of minimising Makespan (Cmax). This objective is considered in this paper because it normally performs well on average with respect to criteria such as due date compliance, total completion time, total tardiness, total flow time, and maximum lateness.

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