Rescheduling Algorithm Based on Rolling Horizon Procedure for a Dynamic Hybrid Flow Shop with Uncertain Processing Time

2015 ◽  
Vol 51 (11) ◽  
pp. 99 ◽  
Author(s):  
Jie ZHANG
Author(s):  
Binghai Zhou ◽  
Wenlong Liu

Increasing costs of energy and environmental pollution is prompting scholars to pay close attention to energy-efficient scheduling. This study constructs a multi-objective model for the hybrid flow shop scheduling problem with fuzzy processing time to minimize total weighted delivery penalty and total energy consumption simultaneously. Setup times are considered as sequence-dependent, and in-stage parallel machines are unrelated in this model, meticulously reflecting the actual energy consumption of the system. First, an energy-efficient bi-objective differential evolution algorithm is developed to solve this mixed integer programming model effectively. Then, we utilize an Nawaz-Enscore-Ham-based hybrid method to generate high-quality initial solutions. Neighborhoods are thoroughly exploited with a leader solution challenge mechanism, and global exploration is highly improved with opposition-based learning and a chaotic search strategy. Finally, problems in various scales evaluate the performance of this green scheduling algorithm. Computational experiments illustrate the effectiveness of the algorithm for the proposed model within acceptable computational time.


Exacta ◽  
2013 ◽  
Vol 11 (2) ◽  
pp. 149-160
Author(s):  
Helio Yochihiro Fuchigami ◽  
João Vitor Moccellin

Neste artigo são apresentados quatro métodos heurísticos construtivos (denominados LPT, TOTAL, SCT e LPST) para programação da produção em sistemas flow shop híbridos com tempos de setup independentes da sequência de execução das tarefas. O foco deste trabalho é o estudo da influência da programação do primeiro estágio neste ambiente de produção. O critério de desempenho utilizado é a minimização da duração total da programação (makespan). O método LPT baseia-se na conhecida regra Longest Processing Time e sequencia as tarefas pela ordem crescente da soma dos tempos de processamento de todos os estágios. O TOTAL utiliza a ideia do Método de Aproximação de Vogel, considerando a matriz composta pela soma dos tempos de processamento e setup de todos os estágios. A denominação SCT foi atribuída a este método por escolher o par tarefa-máquina que conduz à menor data de término (Shortest Completion Time). E o método LPST atribui à máquina de menor carga a tarefa com a maior soma dos tempos de processamento e setup do primeiro estágio. Os resultados da experimentação computacional mostraram que o método SCT foi claramente superior aos demais, com 55,3% de sucesso, enquanto o LPT obteve 26,9%, o TOTAL atingiu 16,4% e por último o LPST apresentou 2,2% de sucesso. Palavras-chave: programação da produção; flow shop híbrido; setup independente. ABSTRACT This paper addresses the hybrid flow shop scheduling problem with sequence-independent setup times. Four constructive heuristic methods (called LPT, TOTAL, SCT and LPST) were proposed with objective to evaluate the influence of the schedule of the first production stage in this environment. The minimization of the total time to complete the schedule (makespan) was used as performance criterion. The LPT method is based on the well-known Longest Processing Time rule and it sequence the jobs by the ascending order of the total processing times of all stages. The TOTAL method uses the idea of Vogel Approximation Method, considering the matrix composed by the sum of processing and setup times of all stages. The SCT method chooses the pair machine-job that leads the Shortest Completion Time. And the LPST method designates to the lower load machine the job with the largest sum of processing and setup times of the first stage. Results of computational experiments reveled that the SCT method was clearly the superior, with 55.3% of success, while LPT obtained 26.9%, TOTAL reached 16.4% and lastly LPST presented 2.2% of success. Keywords: production scheduling; hybrid flow shop; sequence-independent setup time.


2021 ◽  
pp. 1-13
Author(s):  
Orhan Engin ◽  
Mustafa Kerim Yılmaz

In the conventional scheduling problem, the parameters such as the processing time for each job and due dates are usually assumed to be known exactly, but in many real-world applications, these parameters may very dynamically due to human factors or operating faults. During the last decade, several works on scheduling problems have used a fuzzy approach including either uncertain or imprecise data. A fuzzy logic based tool for multi-objective Hybrid Flow-shop Scheduling with Multi-processor Tasks (HFSMT) problem is presented in this paper. In this study, HFSMT problems with a fuzzy processing time and a fuzzy due date are formulated, taking Oğuz and Ercan’s benchmark problems in the literature into account. Fuzzy HFSMT problems are formulated by three-objectives: the first is to maximize the minimum agreement index and the second is to maximize the average agreement index, and the third is to minimize the maximum fuzzy completion time. An efficient genetic algorithm(GA) is proposed to solve the formulated fuzzy HFSMT problems. The feasibility and effectiveness of the proposed method are demonstrated by comparing it with the simulated annealing (SA) algorithm in the literature.


2012 ◽  
Vol 152-154 ◽  
pp. 1487-1491
Author(s):  
Parinya Kaweegitbundit

This paper considers two stage hybrid flow shop with identical parallel machine and evaluate performance of common dispatching rules; shortage processing time (SPT) longest processing time (LPT) earliness due date (EDD) and first in first out (FIFO). The objectives are to determine makespan and total tardiness have been minimized. To evaluated performance of dispatching rules, the results have been compared on each criterion. The experimental results show that SPT outperform than other rules with minimizes makespan as an objective function for all problems. On the other hand, for minimize total tardiness as an objective. The EDD rule outperform than other rules.


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