Development and analysis of priority decision rules using MCDM approach for a flexible job shop scheduling: A simulation study

Thenarasu, M.; Rameshkumar, K.; Rousseau, Jacob; Anbuudayasankar, S.P.

doi:10.1016/j.simpat.2021.102416

Cited by 32 publications

(17 citation statements)

References 47 publications

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“…The ANP method is the expansion of the Analytic Hierarchy Process (AHP), and it is more complex. Moreover, the ANP method can represent different levels of interest of many parties by considering the dependent connection between criteria or alternatives in decision making and various interconnection or dependencies [10], [16], [12], and [21]. Saaty states that the implementation of the ANP problem-solving depends on available alternatives and criteria [22], and [14].…”

Section: The Anp Conceptmentioning

confidence: 99%

“…According to experts, Multi Criteria Decision making (MCDM) is a scientific method that is important in classifying alternatives or for ranking many alternatives into a priority order effectively and efficiently [8]. MCDM technique is a method used to help select decisions from many criteria that can be collaborated with various methods [9] The Fuzzy-based method, such as AHP or ANP [10], [11] and [12], is a technique that allows someone to make decisions and solve problems [10]. Performance evaluation adds a technical point of view for the evaluation process using the Multi-Criteria Decision Making (MCDM) approach [13], Analytical Network Process (ANP), and Choquet Integral software (CI); they demonstrate an efficient way to handle qualitative and quantitative data simultaneously [14].…”

Section: Introductionmentioning

confidence: 99%

“…This study employed the Analytic Network Process (ANP) method, a technique of Multi-Criteria Decision Making (MCDM). This method could present levels and ranks [10], [12], of the importance of various parties by considering available criteria and sub-criteria to predict human resources based on evaluation [15], [16].…”

Section: Introductionmentioning

confidence: 99%

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An Analytic Network Process Method Approach to Design Models of Lecturers Performance Evaluation

Purwani

2022

Int. J. Artif. Intell. Res

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One approach to greatly enhance the quality of university education level is improving the quality and career of lecturers, including services to students. Therefore, performance and work ethic are critically evaluated to obtain re-liable information. Most performance evaluations are limited to assess students in the classroom exclusively. This research employed a Multi-Criteria Decision Making (MCDM), a model designed to evaluate the lecturer’s performance and factors influencing their performance. These factors were examined from various variables, such as training and development experience, motivation, self-esteem, competency, and job satisfaction. To demonstrate the correlation and dependency among factors of lecture performance evaluation, this study employed the Analytic Network Process (ANP) method, which is part of MCDM technique. The ANP method could serve different levels of stakeholders by considering available criteria and sub-criteria. Moreover, the method could predict performance measurement of human resources by considering factors affecting lecturer’s performance. This research produced a model to evaluate lecturers’ performance effectively

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Section: The Anp Conceptmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An Analytic Network Process Method Approach to Design Models of Lecturers Performance Evaluation

Purwani

2022

Int. J. Artif. Intell. Res

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“…The Priority Dispatching Rules (PDRs) are used to prioritize work in a job shop in order to improve performance measures (Thenarasu et al 2022). Sels et al (2012) have discussed various priority rules for JSSP which are compared and validated using different objective functions.…”

Section: Priority Dispatching Rulesmentioning

confidence: 99%

Job shop scheduling using heuristics through Python programming and excel interface

Narayanan¹,

Kumar²,

Potluru³

et al. 2022

Decis. Mak. Appl. Manag. Eng.

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Job shop scheduling problem (JSSP) has remained a challenge both for the practitioners and the researchers. A JSSP consists of multiple number of machines (m) and jobs (n).As the number of jobs increases, the complexity of the problem increases exponentially and it becomes difficult to schedule manually. Many papers in the literature discuss heuristic and metaheuristic solutions to solve Job shop scheduling problems. But there is no ease of use for practitioners who rely on their experience to schedule jobs in ad hoc sessions resulting in inefficient allocation of jobs and machines. In this paper, a job shop scheduling problem under static and dynamic conditions is solved using heuristic approaches using python programming with an MS Excel user interface. For a supplier of automotive parts with a set of jobs and machines, priority dispatching rules, viz., Shortest Processing Time (SPT), Earliest Due Date (EDD), First-In First-Out (FIFO), Critical Ratio (CR) and Slack Per Remaining Operation (S/RO) are evaluated. The obtained performance metrics such as makespan, and tardiness are compared between the heuristics to select an optimal schedule by the job shop. The user inputs the jobs, machines, start and due dates through the MS Excel interface and obtains faster, practically usable results. This reduces the time taken for job scheduling and helps in making faster productivity-based decisions to maximize resource utilization and the total time to produce the product. Integrating Python at the backend and Excel at the front end will encourage many MSMEs to perform optimized scheduling using heuristics thereby reducing the throughput time.

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“…But there are deficiencies in machine assignment such that DRs or other heuristics cannot be used for this sub-problem. Also, the evolutionary process and hence the combination of features for DRs generations is not done in this model [9].…”

Section: Introductionmentioning

confidence: 99%

An Open-Source Simulation Model for Solving Scheduling Problems

Teymourifar¹,

Li²,

Li³

et al. 2022

ujam

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In this study, an open-source simulation model is presented for solving scheduling problems. The model is capable of solving different benchmarks. The methods involved in the simulation are mainly based on generating dispatching rules or using them to solve problems, but there are other heuristics as well. Dispatching rules in an evolutionary process are generated using Gene Expression Programming. For this aim, a coding method, which has not been described in the literature before, is explained. Along with the explanation of the properties of the source code, information about deterministic, dynamic models, buffer states, machine breakdown states, and the methods used to deal with them is presented. Concepts are explained with visual examples. In addition, a subject that has not been investigated in the literature before is analyzed by using the simulation model. This topic is to examine the results of solving machine assignment and operation sequencing sub-problems in flexible job shop scheduling problems with different rules. Moreover, objective functions that the source code can handle are discussed. Unlike many studies in the literature, the codes are presented to the readers as open source. Also, it is open to development and can be easily modified by users to solve other types of problems. Finally, in the study, experimental results are presented on the basis of some benchmarks available in the literature, and the limits of the study and source code are explained.

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Development and analysis of priority decision rules using MCDM approach for a flexible job shop scheduling: A simulation study

Cited by 32 publications

References 47 publications

An Analytic Network Process Method Approach to Design Models of Lecturers Performance Evaluation

An Analytic Network Process Method Approach to Design Models of Lecturers Performance Evaluation

Job shop scheduling using heuristics through Python programming and excel interface

An Open-Source Simulation Model for Solving Scheduling Problems

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