scholarly journals A Dispatching-Fuzzy AHP-TOPSIS Model for Scheduling Flexible Job-Shop Systems in Industry 4.0 Context

2021 ◽  
Vol 11 (11) ◽  
pp. 5107
Author(s):  
Miguel Ortíz-Barrios ◽  
Antonella Petrillo ◽  
Fabio De Felice ◽  
Natalia Jaramillo-Rueda ◽  
Genett Jiménez-Delgado ◽  
...  
Keyword(s):  
Job Shop ◽  
Selection Process ◽  
Fuzzy Ahp ◽  
Flexible Job Shop ◽  
Criteria Weights ◽  
Dispatching Algorithm ◽  
Scheduling Method ◽  
Hard Problems ◽  
Fourth Step

Scheduling flexible job-shop systems (FJSS) has become a major challenge for different smart factories due to the high complexity involved in NP-hard problems and the constant need to satisfy customers in real time. A key aspect to be addressed in this particular aim is the adoption of a multi-criteria approach incorporating the current dynamics of smart FJSS. Thus, this paper proposes an integrated and enhanced method of a dispatching algorithm based on fuzzy AHP (FAHP) and TOPSIS. Initially, the two first steps of the dispatching algorithm (identification of eligible operations and machine selection) were implemented. The FAHP and TOPSIS methods were then integrated to underpin the multi-criteria operation selection process. In particular, FAHP was used to calculate the criteria weights under uncertainty, and TOPSIS was later applied to rank the eligible operations. As the fourth step of dispatching the algorithm, the operation with the highest priority was scheduled together with its initial and final time. A case study from the smart apparel industry was employed to validate the effectiveness of the proposed approach. The results evidenced that our approach outperformed the current company’s scheduling method by a median lateness of 3.86 days while prioritizing high-throughput products for earlier delivery.

scholarly journals Evaluation of Influenza Intervention Strategies in Turkey with Fuzzy AHP-VIKOR

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Funda Samanlioglu
Keyword(s):  
Fuzzy Ahp ◽  
Intervention Strategy ◽  
Multiple Criteria Decision Making ◽  
Intervention Strategies ◽  
Analytic Hierarchy ◽  
Medicine Physician ◽  
Criteria Weights ◽  
Hierarchy Process ◽  
Internal Medicine Physician

In this study, a fuzzy AHP-VIKOR method is presented to help decision makers (DMs), especially physicians, evaluate and rank intervention strategies for influenza. Selecting the best intervention strategy is a sophisticated multiple criteria decision-making (MCDM) problem with potentially competing criteria. Two fuzzy MCDM methods, fuzzy analytic hierarchy process (F-AHP) and fuzzy VIsekriterijumska optimizacija i KOmpromisno Resenje (F-VIKOR), are integrated to evaluate and rank influenza intervention strategies. In fuzzy AHP-VIKOR, F-AHP is used to determine the fuzzy criteria weights and F-VIKOR is implemented to rank the strategies with respect to the presented criteria. A case study is given where a professor of infectious diseases and clinical microbiology, an internal medicine physician, an ENT physician, a family physician, and a cardiologist in Turkey act as DMs in the process.

scholarly journals Sequential Scheduling Method for FJSP with Multi-Objective under Mixed Work Calendars

Processes ◽  
2019 ◽  
Vol 7 (12) ◽  
pp. 888
Author(s):  
Qiang Zeng ◽  
Menghua Wang ◽  
Ling Shen ◽  
Hongna Song
Keyword(s):  
Job Shop ◽  
Job Shop Scheduling ◽  
Scheduling Problem ◽  
Genetic Operators ◽  
Nsga Ii ◽  
Multi Objective ◽  
Elite Strategy ◽  
Scheduling Method ◽  
Encoding Method

A sequential scheduling method for multi-objective, flexible job-shop scheduling problem (FJSP) work calendars is proposed. Firstly, the sequential scheduling problem for the multi-objective FJSP under mixed work calendars was described. Secondly, two key technologies to solve such a problem were proposed: one was a time-reckoning technology based on the machine’s work calendar, the other was a sequential scheduling technology. Then, a non-dominated sorting genetic algorithm with an elite strategy (NSGA-II) was designed to solve the problem. In the algorithm, a two-segment encoding method was used to encode the chromosome. A two-segment crossover and mutation operator were used with an improved strategy of genetic operators therein to ensure feasibility of the chromosomes. Time-reckoning technology was used to calculate start and end time of each process. The sequential scheduling technology was used to implement sequential scheduling. The case study shows that the proposed method can obtain an effective Pareto set of the sequential scheduling problem for multi-objective FJSP under mixed work calendars within an acceptable time.

S1440102 A Flexible Job Shop Scheduling Method Using Genetic Algorithm

2015 ◽  
Vol 2015 (0) ◽  
pp. _S1440102--_S1440102-
Author(s):  
Yuki SAKAGUCHI ◽  
Eiji MORINAGA ◽  
Hidefumi WAKAMATSU ◽  
Eiji ARAI
Keyword(s):  
Genetic Algorithm ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Flexible Job Shop ◽  
Flexible Job Shop Scheduling ◽  
Shop Scheduling ◽  
Scheduling Method

scholarly journals SOLVING RESOURCE-CONSTRAINED CONSTRUCTION SCHEDULING PROBLEMS WITH OVERLAPS BY METAHEURISTIC

2014 ◽  
Vol 20 (5) ◽  
pp. 649-659 ◽  
Author(s):  
Wojciech Bożejko ◽  
Zdzisław Hejducki ◽  
Mariusz Uchroński ◽  
Mieczysław Wodecki
Keyword(s):  
Assembly Line ◽  
Flow Shop ◽  
Construction Process ◽  
Scheduling Problems ◽  
Construction Scheduling ◽  
Efficient Construction ◽  
Scheduling Method ◽  
Hard Problems ◽  
Reducing Costs

The paper concerns the problem of roadworks scheduling executed in the flow-shop system. Works may be performed parallelly with the acceleration (overlaps) of construction project, i.e. the following work on the assembly line can begin before the completion of the predecessor work. Taking into account the acceleration enables accurate modeling of complex real construction processes. The above fact can greatly shorten the time of realization of construction process which has a direct impact on reducing costs. The considered issue belongs to the class of NP-hard problems. We introduce the new: mathematical model, specific properties as an acceleration tools, as well as two new optimization algorithms for the problem considered: construction and tabu search. The execution of algorithms was illustrated on the example of a case study concerning the construction of roads. They were also verified on the examples taken from the literature and on already completed construction processes. The obtained results are fully satisfactory. The assigned execution times are close to optimal. The presented methods allow its practitioners (both the planners and the managers) to include in the model the acceleration of the works and the design of a much more efficient construction scheduling. The presented new scheduling method leads to a more competitive environment for contraction companies.

Petri Net with Uncontrollable Transition and GA Based Approach for JSP

2011 ◽  
Vol 48-49 ◽  
pp. 824-829
Author(s):  
Tao Ze ◽  
Xiao Xia Liu
Keyword(s):  
Petri Net ◽  
Completion Time ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Flexible Job Shop ◽  
Scheduling Problem ◽  
Flexible Job Shop Scheduling ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Scheduling Method

A new dual-objective scheduling method based on the controlled Petri net and GA is proposed to the job-shop scheduling problem (JSP) with urgent orders constrained by machines, workers. Firstly, a controller designed method for Petri net with uncontrollable transition is introduced, and based on the method, the Petri net model is constructed for urgent jobs in flexible job shop scheduling problem. Then, the genetic algorithm (GA) is applied based on the controlled Petri net model and Pareto. Function objectives of the proposed method are to minimize the completion time and the total expense of machines and workers. Finally, Scheduling example is employed to illustrate the effectiveness of the method.

Modeling and Scheme Generation of Dynamic Flexible Job-Shop Scheduling

2013 ◽  
Vol 423-426 ◽  
pp. 2232-2236
Author(s):  
Ying Pan ◽  
Dong Juan Xue ◽  
Tian Yi Gao ◽  
Li Bin Zhou ◽  
Xiao Yu Xie
Keyword(s):  
Dynamic Simulation ◽  
Job Shop ◽  
Dynamic Scheduling ◽  
Job Shop Scheduling ◽  
Adaptive Genetic Algorithm ◽  
Flexible Job Shop ◽  
Uncertain Information ◽  
Flexible Job Shop Scheduling ◽  
Shop Scheduling ◽  
Scheduling Method

Aiming at uncertain information and dynamic characteristic during flexible job-shop scheduling process, some kind of dynamic scheduling method for flexible job-shop scheduling problem (FJSP) is put forward based on real-time adjustment. A dynamic simulation solution mode framework is presented for FJSP. This framework is inspired by adaptive control, combined with the robust scheduling and foreseeing scheduling. It has both advantages of such two scheduling methods, and its stable and highly efficient. Preliminary scheme generation method based on foreseeing dynamics scheduling is introduced then. Foreseeing function is realized by fault-handling algorithm and dynamic simulation solver on the basis of Adaptive Genetic Algorithm (AGA).

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