Soft-computing approaches for rescheduling problems in a manufacturing industry

被引:9
|
作者
Acevedo-Chedid, Jaime [1 ]
Grice-Reyes, Jennifer [1 ]
Ospina-Mateus, Holman [1 ]
Salas-Navarro, Katherinne [2 ]
Santander-Mercado, Alcides [3 ]
Sana, Shib Sankar [4 ]
机构
[1] Univ Tecnol Bolivar, Dept Ind Engn, Cartagena, Colombia
[2] Univ Costa, Dept Prod & Innovat, Barranquilla, Colombia
[3] Univ Norte, Dept Ind Engn, Barranquilla, Colombia
[4] Kishore Bharati Bhagini Nivedita Coll, Kolkata 700060, India
基金
美国国家卫生研究院;
关键词
Flexible manufacturing system; scheduling; reactive scheduling; Petri net; memetics algorithm; GENETIC ALGORITHM; PETRI NETS; SEARCH ALGORITHM; SYSTEMS; MODEL; FMS; INVENTORY; SELECTION; SUBJECT;
D O I
10.1051/ro/2020077
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
Flexible manufacturing systems as technological and automated structures have a high complexity for scheduling. The decision-making process is made difficult with interruptions that may occur in the system and these problems increase the complexity to define an optimal schedule. The research proposes a three-stage hybrid algorithm that allows the rescheduling of operations in an FMS. The novelty of the research is presented in two approaches: first is the integration of the techniques of Petri nets, discrete simulation, and memetic algorithms and second is the rescheduling environment with machine failures to optimize the makespan and Total Weighted Tardiness. The effectiveness of the proposed Soft computing approaches was validated with the bottleneck of heuristics and the dispatch rules. The results of the proposed algorithm show significant findings with the contrasting techniques. In the first stage (scheduling), improvements are obtained between 50 and 70% on performance indicators. In the second stage (failure), four scenarios are developed that improve the variability, flexibility, and robustness of the schedules. In the final stage (rescheduling), the results show that 78% of the instances have variations of less than 10% for the initial schedule. Furthermore, 88% of the instances support rescheduling with variations of less than 2% compared to the heuristics.
引用
收藏
页码:S2125 / S2159
页数:35
相关论文
共 50 条
  • [1] Comparison of conventional approaches and Soft-Computing approaches for Software Quality Prediction
    Baisch, E
    Liedtke, T
    SMC '97 CONFERENCE PROCEEDINGS - 1997 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-5: CONFERENCE THEME: COMPUTATIONAL CYBERNETICS AND SIMULATION, 1997, : 1045 - 1049
  • [2] Innovative Soft-Computing Solutions for Industrial and Environmental Problems
    Herrero, Alvaro
    Cambra, Carlos
    Bayraktar, Secil
    Jimenez, Alfredo
    Corchado, Emilio
    CYBERNETICS AND SYSTEMS, 2023, 54 (03) : 267 - 269
  • [3] Medical Image Examination using Traditional and Soft-computing Approaches
    Rajinikanth, Venkatesan
    CURRENT MEDICAL IMAGING, 2020, 16 (07) : 775 - 775
  • [4] Soft-Computing in Antennas & Propagation
    Mishra, Rabindra K.
    INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN MICROWAVE THEORY AND APPLICATIONS, PROCEEDINGS, 2008, : 142 - 143
  • [5] Applying soft-computing techniques in solving dynamic multi-objective layout problems in cellular manufacturing system
    Ghosh, Tamal
    Doloi, B.
    Dan, Pranab K.
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2016, 86 (1-4): : 237 - 257
  • [6] Applying soft-computing techniques in solving dynamic multi-objective layout problems in cellular manufacturing system
    Tamal Ghosh
    B. Doloi
    Pranab K. Dan
    The International Journal of Advanced Manufacturing Technology, 2016, 86 : 237 - 257
  • [7] Application of soft-computing technologies to the traffic control system design problems
    Yusupbekov, N. R.
    Marakhimov, A. R.
    Iganaberdiev, H. Z.
    Umarov, Sh. X.
    12TH INTERNATIONAL CONFERENCE ON APPLICATION OF FUZZY SYSTEMS AND SOFT COMPUTING, ICAFS 2016, 2016, 102 : 540 - 546
  • [8] Special issue: Soft computing approaches to manufacturing
    Monostori, L
    JOURNAL OF INTELLIGENT MANUFACTURING, 1998, 9 (04) : 279 - 280
  • [9] Demand Prediction Using a Soft-Computing Approach: A Case Study of Automotive Industry
    Eloy Salais-Fierro, Tomas
    Astrid Saucedo-Martinez, Jania
    Rodriguez-Aguilar, Roman
    Manuel Vela-Haro, Jose
    APPLIED SCIENCES-BASEL, 2020, 10 (03):
  • [10] A soft-computing framework for fault diagnosis
    Rajagopalan, C
    Raj, B
    Kalyanasudaram, P
    INFORMATION SCIENCES, 2000, 127 (3-4) : 87 - 100