Integrating simulation and FITradeoff method for scheduling rules selection in job-shop production systems

Pergher, Isaac; Frej, Eduarda Asfora; Roselli, Lucia Reis Peixoto; Almeida, Adiel Teixeira de

doi:10.1016/j.ijpe.2020.107669

Cited by 45 publications

(16 citation statements)

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“…The FITradeoff method has been made use of in a wide range of practical applications. Thus, it was used in medical applications (Dell'Ovo et al, 2020;Camilo et al 2020), in energy applications (Fossile et al, 2020;de Macedo, de Miranda-Mota and Sola, 2018;Kang, Frej and de Almeida, 2018), in environmental applications (Monte and Morais, 2019;Carrillo et al, 2018), in a security application (Camara e Silva et al, 2019), and in industry applications (Frej, de Almeida and Costa, 2017;Santos et al, 2020;Pergher et al, 2020; Silva, Costa and Frej, de Almeida and Costa, 2019;Lima, Viegas and Costa, 2017;de Gusmão and Pereira Medeiros, 2016). In order to test the performance of the FITradeoff method, Mendes et al (2020) performed simulation studies considering several scenarios, including different number of criteria and alternatives.…”

Section: Introductionmentioning

confidence: 99%

Using the FITradeoff method to solve a shopping mall location problem in the northeastern countryside of Brazil

Ribeiro

Roselli

Frej

et al. 2021

Control and Cybernetics

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This paper presents a practical case involving a shopping mall location problem in the northeast countryside of Brazil. In this problem, conflicting objectives have been expressed in terms of seven criteria. Then, ten cities of the northeastern countryside have been selected to compose the space of actions. The problem plays a special role since Brazil is a big country that requires investments in the countryside. Thus, the shopping mall aims to stimulate economic growth in the respective region. In the study, this multi-objective problem is solved using the FITradeoff method. In FITradeoff, the combination of the paradigms of holistic evaluation and elicitation by decomposition in preference modeling are well explored, bringing different perspectives for the decision-maker during the decision process.

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Section: Introductionmentioning

confidence: 99%

Using the FITradeoff method to solve a shopping mall location problem in the northeastern countryside of Brazil

Ribeiro

Roselli

Frej

et al. 2021

Control and Cybernetics

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“…In Pergher et al. (2020), the FITradeoff method is applied to define the best combination of scheduling decisions which are: due date assignment, order release, and priority dispatching. Silva et al.…”

Section: Literature Reviewmentioning

confidence: 99%

“…(2021), in which several cases are described (e.g. Frej et al., 2017; Carrillo et al., 2018; Pergher et al., 2020), discussing whether it is appropriate to use visualizations to conduct the decision‐making process. In de Almeida et al.…”

Section: The Success‐based Decision Rulementioning

confidence: 99%

The use of the success‐based decision rule to support the holistic evaluation process in FITradeoff

Roselli

Almeida

2021

Int Trans Operational Res

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The flexible and interactive tradeoff (FITradeoff) method is a multi-criteria decision-making/aiding (MCDM/A) method in the context of the multi-attribute value theory. The implementation of the FITradeoff method is supported by a decision support system (DSS), which includes an elicitation procedure for scaling constants with the flexibility of including a holistic evaluation. The holistic evaluation has graphics that can be used to assist decision-makers (DMs) during the FITradeoff decision process. In this context, three neuroscience experiments have been conducted to investigate how a DM uses the graphics to evaluate an MCDM/A problem. Thus, the main contribution of this paper is to propose the success-based decision rule. Based on this rule, recommendations are made concerning the holistic evaluation. The first is that this rule can assist the analyst to advise DMs with information on the visualization's probability of success. Second, this rule suggests improvements that can be made to the design of the FITradeoff DSS.

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“…In recent years, the technological advancements in computer simulation as an appropriate approach have guaranteed the feasibility and effectiveness of the designed process plan in a variety of engineering issues [25]. The use of simulation for real-time decision making directly in the manufacturing process is commonly employed before launching a new production [26]. A DES model enables the analysis of the dynamic of the stochastic system.…”

Section: Desmentioning

confidence: 99%

Simulation-Based Optimization using DEA and DOE in Production System

2021

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Production System (PS) is the process of planning, organizing, directing and controlling the tactical and strategic planning of the different components of the company, to transform inputs into finished products which must be effectively managed. Important parts of PS that always face major challenges in manufacturing systems include production strategy, resource allocation, logistics and production planning. Because of the importance of examining the various components of PS and evaluating its performance on key indicators of organization, it is necessary to evaluate the impact of any changes in these elements to the system prior to its creation. In this regard, the present study aimed to increasing the efficiency and determining the useful methods to evaluate and optimize the performance in different part of PS. To this end, an integrated Discrete-Event Simulation (DES), Design of Experiments (DOE), Data Envelopment Analysis (DEA), and Multi-Attribute Decision Making (MADM) models were implemented to analyze and optimize the real PS process. In the case study of the automobile manufacturing industry in Iran, the accurate analysis was applied to the proposed approach and its different aspects were considered as well. The results indicated that the proposed approach is a practical way for evaluating and optimizing the performance of different part of PS, compared to previous models and helps the manufacturing companies to make efficient decisions regarding increasing productivity while decreasing the essential problems.

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Integrating simulation and FITradeoff method for scheduling rules selection in job-shop production systems

Cited by 45 publications

References 30 publications

Using the FITradeoff method to solve a shopping mall location problem in the northeastern countryside of Brazil

Using the FITradeoff method to solve a shopping mall location problem in the northeastern countryside of Brazil

The use of the success‐based decision rule to support the holistic evaluation process in FITradeoff

Simulation-Based Optimization using DEA and DOE in Production System

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