Evaluation and Selection of Best Priority Sequencing Rule in Job Shop Scheduling using Hybrid MCDM Technique

Kumar, Kalla Kiran; Nagaraju, Dega; Gayathri, S.; Narayanan, Swathi Jamjala

doi:10.1088/1757-899x/197/1/012059

Cited by 11 publications

(11 citation statements)

References 14 publications

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“…Hafez et al (2018) evaluated the performance of dispatching rules when different number of jobs and machines are considered based on minimum total completion time. Kumar et al (2017) considered seven different sequencing rules in a problem related to job shop scheduling. The authors applied a hybrid MCDM technique like analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) to rank sequencing rules.…”

Section: Scheduling Problemsmentioning

confidence: 99%

“…In this section, data for scheduling and sequencing problem from a previous literature of Kumar et al (2017) is considered. The authors in their work demonstrated the method of calculating and choosing the finest sequencing rule by using hybrid MCDM technique i.e.…”

Section: Numerical Illustrationmentioning

confidence: 99%

“…A research of the relevant literature yielded, the PSI has not been implemented on scheduling and sequencing problems in a job shop. In this article, the problem from Kumar et al (2017) is considered and solved using the PSI. The result obtained from the PSI are compared with the previous researchers' results.…”

Section: Introductionmentioning

confidence: 99%

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Ranking of sequencing rules in a job shop scheduling problem with preference selection index approach

Bari¹,

Karande²

2022

J. Decis. Anal. Int. Comp.

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Scheduling different jobs in an appropriate sequence are very important in manufacturing industries due to the influence of conflicting criteria. It becomes difficult to sequence the jobs as the job number increases due to numerous computations involved. In this article, six jobs are considered to be treated on a machine one by one. Seven different priority sequencing rules provide seven different sequencing options for the jobs which are assessed using a set of nine criteria. Preference selection index (PSI) approach, a multi-criterion decision-making (MCDM) technique is proposed to rank them from best to worst. The PSI approach, unlike other MCDM methods, does not require to find the relative significance of the criteria, which reduces work of finding weights of criteria hence is a very easy and effective tool for decision making. A benchmark problem from the previous literature is considered and solved using the PSI approach and the obtained results are found to be correct.

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Section: Scheduling Problemsmentioning

confidence: 99%

Section: Numerical Illustrationmentioning

confidence: 99%

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Ranking of sequencing rules in a job shop scheduling problem with preference selection index approach

Bari¹,

Karande²

2022

J. Decis. Anal. Int. Comp.

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“…Two decision-making methods were used for this study: the analytic hierarchy process (AHP) and data envelopment analysis (DEA). AHP is a multi-objective decision-making method that enables the analysis of qualitative and quantitative data [29,30] whilst DEA categorizes the criteria used as inputs and outputs, where the factors that need to be minimized are placed as inputs and the factors to be maximized are placed as outputs [31,32].…”

Section: Multi-criteria Decision-makingmentioning

confidence: 99%

Selection of Production Mix in the Agricultural Machinery Industry Considering Sustainability in Decision Making

2021

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Competition among companies is growing globally, with the need to increase productivity and efficiency in the product sector. However, there is also a growing concern about global warming and the depletion of natural resources, as well as their effects on human health. In this context, all human activities that involve intense usage of resources must take into account sustainability as one of the decision criteria. This work presents the application of decision-making methods to define the best product mix in the agricultural machinery industry. With this objective, the current schedule of the production line was identified, along with the production flow, by performing an inventory analysis and an environmental impact study (endpoint). A total of seven alternatives for the production mix of grain trailers were defined, considering different materials and production processes. The selection of the best schedule according to the different criteria was performed through the analytic hierarchy process (AHP) and data envelopment analysis (DEA) to evaluate the managerial implications for decision making. The results obtained through AHP identified a single alternative as being the best, which facilitates the decision making. The DEA method identified two alternatives as the most efficient, and in this case the manager can choose between a product mix that generates lesser environmental impact or greater profitability. Although applied to agricultural industry, the presented methodology can be easily adapted to other activities related to the built environment, such as construction industry.

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“…Leu and Yang [43] adopted an integration of Genetic Algorithm and TOPSIS, in which Genetic Algorithm processes overall calculations to solve the problem and TOPSIS strives to balance multiple cost and time consumption objectives. Kiran Kumar [44] integrated AHP and TOPSIS methods, where AHP calculates weights of the criteria (objective functions) according to the assessments of decision makers and supplies the weights to TOPSIS method, and TOPSIS sorts priority dispatching rules according to their ranks. In their study, Jadhav and Bajaj [45] had a different approach, so that TOPSIS is determining the processing orders jobs.…”

Section: Solving Fssp With Mcdmmentioning

confidence: 99%

An Integrated Solution Approach for Flow Shop Scheduling

Karacan

Şenvar

et al. 2021

Teh. vjesn.

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This study seeks to integrate Random Key Genetic Algorithm (RKGA) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) to compute makespan and solve the Flow Shop Scheduling Problem (FSSP). FSSP is considered as a Multi Criteria Decision Making Problem (MCDM) by setting machines as criteria and jobs as alternatives. RKGA is employed to determine the best weights for the criteria that directly affect the robustness of the solution. The proposed methodology is presented with illustrative example and applied to benchmark problems. The solutions are compared to well-known construction heuristics. The proposed methodology provides the best or reasonable solutions in acceptable computational times.

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Evaluation and Selection of Best Priority Sequencing Rule in Job Shop Scheduling using Hybrid MCDM Technique

Cited by 11 publications

References 14 publications

Ranking of sequencing rules in a job shop scheduling problem with preference selection index approach

Ranking of sequencing rules in a job shop scheduling problem with preference selection index approach

Selection of Production Mix in the Agricultural Machinery Industry Considering Sustainability in Decision Making

An Integrated Solution Approach for Flow Shop Scheduling

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