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This paper presents a simulated genetic algorithm model of scheduling the flow shop problems with re-entrant jobs. The objectives of this research are to minimize the weighted tardiness and makespan. The proposed model considers that the jobs with non-identical due dates are processed on the machines with the same order. Furthermore, the re-entrant jobs are stochastic as only some jobs are required...
A new flow shop scheduling problem (FSP) is studied, which is abstracted from the auto assemble workshop. The problem is characterized by multi-workstation operation and stopping-line operation, and fluctuant processing time. It is a typical NP-hard optimization problem with strong industrial roots. Firstly, the mathematical model of this scheduling problem is constructed. And then the scheduling...
A new flow shop scheduling problem (FSP) is studied, which is abstracted from the auto assemble workshop. The problem is characterized by multi-workstation operation and stopping line operation, and fluctuant processing time. So the problem is very complicated. Firstly, the math model of this scheduling problem is constructed, and then the Petri net model is constructed based on the math model. The...
The flow shop scheduling problem (FSSP) is a NP-HARD combinatorial problem with strong industrial background. Among the meta-heuristics, genetic algorithms attracted a lot of attention. However, lacking the major evolution direction, the effectiveness of regular genetic algorithm is restricted. In this paper, the particle swarm optimization algorithm (PSO) is introduced for better initial group. By...
In this paper, the mixed-integer nonlinear programming model is established for hybrid flow-shop scheduling problem (HFSP), with the minimum of energy consumption as the objective function. Aiming at the characteristic of this problem and the shortcomings of simple genetic algorithm, a hybrid genetic algorithm (Memetic) is presented. To validate the preciseness of the model and the availability of...
No-wait flowshops with flowtime minimization are typical NP-complete combinatorial optimization problems, widely existing in practical manufacturing systems. Different from traditional methods by which objective of a new schedule being completely computed objective increment methods are presented in this paper by which the objective of an offspring being obtained just by objective increments and computational...
Multi-objective flowshop scheduling problems have gained wide attention both in practical and academic fields. In this paper, a hybrid multi-objective genetic algorithm is proposed to solve multi-objective no-wait flowshop scheduling problems with both the makespan and the total flow time minimization. The proposed algorithm makes use of the principle of non-dominated sorting, coupled with the use...
Numerous real-world problems relating to flow-shop scheduling are characterized by combinatorially explosive alternatives as well as multiple conflicting objectives and are denoted as multiobjective combinatorial optimization problems. The problem of multiobjective optimization with setup times in flow shop is considered in this study. The objective function of the problem is minimization of the weighted...
Production scheduling has been recognized as common but challenging combinatorial problems. Because of their complexity, recent research has turned to genetic algorithms to address such problems. Although genetic algorithms have been proven to facilitate the entire space search, they lack in fine-tuning capability for obtaining the global optimum. Therefore, in this study a hybrid genetic algorithm...
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