Using of evolving cellular automata for flexible job shop with makespan criterion

Antczak, A.; Antczak, Paweł; Witkowski, Tadeusz

doi:10.1109/idaacs.2009.5342977

Cited by 4 publications

(3 citation statements)

References 24 publications

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“…In 2009, Witkowski, from Warsaw University Technology, used evolving cellular automata for flexible job shop with a makespan criterion and applied data mining to explore the regularities of CA in scheduling [55]. Abdolzadeh, from Islamic Azad University, combined cellular automata and a reinforcement learning algorithm for the first time and applied cellular learning automata to solve the job-shop scheduling problem: by generating actions based on received responses from the problem environment, the appropriate position for operation of jobs was chosen in execution sequence [56].…”

Section: Research Interests: Production Scheduling Problems In Manufamentioning

confidence: 99%

Academic Insights and Perspectives: Cellular Automata and Production Scheduling

Chen

Cheng

et al. 2020

Mathematical Problems in Engineering

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The cellular automata algorithm is one of the most important developments recently and is becoming an area of great potential in scheduling problems. There has been an increase in the quality and quantity of publications related to this topic. To formally illustrate the research status of the cellular automata algorithm at the global level, bibliometric analysis was used based on the Web of Science and Scopus databases, and 3086 documents were retrieved from different countries and regions. Institutions, journals, authors, research areas, author keywords, and highly cited articles are discussed in detail. The results show that the USA and China are the dominant countries in this field. The USA is the most active country cooperating with other 47 countries or regions, especially with China. The Journal of Cellular Automata is the most productive journal in this field, and the Democritus University of Thrace is the most productive institution also with the highest h-index. “Computer Science” is the most investigated area, with 544 documents involved. In addition, the major topics focused by author keywords are “genetic algorithm,” “swarm intelligence,” and “evolutionary computation.” In addition, the cellular automata algorithm is viewed as a new and effective method to solve the scheduling problems in manufacturing system; meanwhile, historical developments of the application of cellular automata in scheduling are displayed and analyzed.

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Section: Research Interests: Production Scheduling Problems In Manufamentioning

confidence: 99%

Academic Insights and Perspectives: Cellular Automata and Production Scheduling

Chen

Cheng

et al. 2020

Mathematical Problems in Engineering

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“…The use of evolving CA in solving flexible job shop scheduling was proposed by Antczak et al 16 The authors proposed an algorithm based on Seredyński et al’s approach of CA with an extension. The algorithm generates schedules based on two CA.…”

Section: Motivation and Backgroundmentioning

confidence: 99%

Cellular Automata approach for parallel machine scheduling problem

et al. 2016

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The aim of the paper is to present a new approach based on the Cellular Automata technique for a specific class of scheduling problems with parallel machines (in which some important parameter values cannot be determined a priori). The problem domain is represented by an asynchronous non-homogeneous cellular automaton. In addition, the division of the method into three levels is introduced. Inseparable use of simulation, optimization and result levels, is proposed. To illustrate our proposition, the optimization problem of drilling tunnels in a given area is considered. A number of simulation experiments were performed involving different instances of the problem and the results are presented and discussed in the paper.

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“…The adaptation of cellular automata to solve parallel scheduling problems was first described by Seredyn´ski and colleagues, [12][13][14] Vidica and de Oliveira, 15 and Draa and Meshoul. 16 The next proposition for using cellular automata to solve scheduling problems is described by M Abdolzadeh and H Rashidi 17 and Antczak et al 18 In these papers, the application of cellular automata (CA) technique to solve job shop problems was presented. Solving scheduling problems using constraint programming (CP) is also very popular, especially in production scheduling, project planning, and transport problems.…”

Section: Motivation and Backgroundmentioning

confidence: 99%

Algebraic-logical meta-model based approach for scheduling manufacturing problem with defects removal

Kucharska

Grobler-Dębska

Rączka

2017

Advances in Mechanical Engineering

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The article deals with a formal approach to solving manufacturing problem with defects removal and presents the application of this approach to flow-shop system with defects. The defects are detected during quality control and thus they are unexpected events. Moreover, a job processing time is not predetermined, and it may contain the unknown time needed to repair. Therefore, stochastic uncertainties are considered, but in addition, we model the process of decision making. The algebraic-logical meta-model methodology constitutes the basis for our approach. A hybrid algorithm for constructing a solution based on the process simulation using special local optimizing task and algebraic-logical models switching when defect detection occurs is presented. In particular, the following elements of the presented approach are shown: disturbances type analyzing, definition of switching states set, definition of subproblems, algebraic-logical metamodels creating for all subproblems, switching types determining, determination of the switching rules, the switching function, and components of special local criterion definition. The article shows results of computer experiments.

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Using of evolving cellular automata for flexible job shop with makespan criterion

Cited by 4 publications

References 24 publications

Academic Insights and Perspectives: Cellular Automata and Production Scheduling

Academic Insights and Perspectives: Cellular Automata and Production Scheduling

Cellular Automata approach for parallel machine scheduling problem

Algebraic-logical meta-model based approach for scheduling manufacturing problem with defects removal

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