Mathematical Modeling and Discrete Firefly Algorithm to Optimize Scheduling Problem with Release Date, Sequence-Dependent Setup Time, and Periodic Maintenance

Qamhan, Mustafa A.; Qamhan, Ammar A.; Al-Harkan, Ibrahim M.; Alotaibi, Yousef Ajami

doi:10.1155/2019/8028759

Cited by 8 publications

(6 citation statements)

References 39 publications

(57 reference statements)

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“…In other words, this paper deals with larger and empirical sets of data that contain more constraints, which made it more realistic. In this research, the parameters covered a wider base than those in other studies, e.g., the setup time was 1-10 in the study such in Afzalirad and Rezaeian [36] and Qamhan et al [37], while in this study, the setup time is divided into four categories of 1-9, 1-49, 1-99, and 1-124. Furthermore, the processing time in this study was 1-99 but in other studies was 1-50.…”

Section: Introductionmentioning

confidence: 75%

Modified Harmony Search Algorithm for Resource-Constrained Parallel Machine Scheduling Problem with Release Dates and Sequence-Dependent Setup Times

et al. 2021

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This research focuses on the problem of scheduling a set of jobs on unrelated parallel machines subject to release dates, sequence-dependent setup times, and additional renewable resource constraints. The objective is to minimize the maximum completion time (makespan). To optimize the problem, a modified harmony search (MHS) algorithm was proposed. The parameters of MHS are regulated using full factorial analysis. The MHS algorithm is examined, evaluated, and compared to the best methods known in the literature. Four algorithms were represented from similar works in the literature. A benchmark instance has been established to test the sensitivity and behavior of the problem parameters of the different algorithms. The computational results of the MHS algorithm were compared with those of other metaheuristics. The competitive performance of the developed algorithm is verified, and it was shown to provide a 42% better solution than the others.

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Section: Introductionmentioning

confidence: 75%

Modified Harmony Search Algorithm for Resource-Constrained Parallel Machine Scheduling Problem with Release Dates and Sequence-Dependent Setup Times

et al. 2021

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“…Under the objective of minimizing a maximum lateness minimization [25] and minimizing the makespan [26], different algorithms were presented to solve the problem, the results showing their effectiveness. Likewise, Qamhan et al also presented an evolutionary discrete firefly algorithm (EDFA) to solve a real-world manufacturing system problem of job scheduling [27]. Touat et al focused on flexible maintenance under human resource constraints on single machine scheduling problems to minimize the sum of total weighted tardiness [28].…”

Section: Literature Reviementioning

confidence: 99%

An Exact Method and Ant Colony Optimization for Single Machine Scheduling Problem With Time Window Periodic Maintenance

et al. 2020

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This paper considers a time window periodic maintenance strategy with different duration windows and job scheduling activities in a single machine environment. The aim is to minimize the number of tardy jobs through the integration of production scheduling and periodic maintenance intervals. A mixedinteger linear programming model (MILP) is proposed to optimize small-sized test instances. Furthermore, an ant colony optimization (ACO) algorithm is developed to solve larger sized test instances. Subsequently, to measure the efficiency of the solutions obtained by ACO, Moore's algorithm is also developed to benchmark with ACO. To test the efficiency and the effectiveness of the ACO algorithm, a set of data for small and large sized problems was generated in which several parameters were adopted and then ten replicates were solved for each combination. The small sized instances were solved by the MILP. Then, the results obtained showed that the proposed ACO was able to obtain the exact solutions within reasonable CPU times, thus, it outperformed the CPLEX solver with respect to CPU. The large sized instances were solved by the Moore's algorithm and compared to ACO. Then, the results obtained showed that the ACO outperforms Moore's algorithm for all the instances tested. It can be concluded that the developed ACOis very efficient and effective in solving the problem considered in this paper. INDEX TERMS Scheduling, MILP, single machine, periodic Maintenance, ant colony. AHMED BADWELAN received the B.Sc. degree in mechanical engineering from the Faculty of Engineering, University of Aden, in 2012, and the M.S. degree in industrial engineering from King Saud University, Saudi Arabia. He is currently pursuing the Ph.D. degree with the

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“…This lower bound is presented in the work of Qamhan et al [45]. The property depends on the latest release date and given as follows For any feasible schedule s, max i (r i + P i + S i ) ≤ C max Note: The lower bound of the problem is estimated by the maximum value between these three properties.…”

Section: ) Second Lower Boundmentioning

confidence: 99%

Optimize Unrelated Parallel Machines Scheduling Problems With Multiple Limited Additional Resources, Sequence-Dependent Setup Times and Release Date Constraints

Al-Harkan

Qamhan

2019

IEEE Access

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This paper considers the problem of scheduling a set of jobs on unrelated parallel machines subject to several constraints which are non-zero arbitrary release dates, limited additional resources, and non-anticipatory sequence-dependent setup times. The objective function is to minimize the maximum completion time. In order to find an optimal solution for this problem, a new mixed-integer linear programming model (MILP) is presented. Moreover, a two-stage hybrid metaheuristic based on variable neighborhood search hybrid and simulated annealing (TVNS_SA) is proposed. In the first stage, a developed heuristic is used to find an initial solution with good quality. At the second stage, the obtained initial solution is used as the first neighborhood structures in the proposed metaheuristic, for further progress different neighborhood structures and effective resolution schemes are also presented. The computational results indicate that the proposed metaheuristic is capable of obtaining optimal solutions for most of the instances when compared to the solution obtained by the developed mixed-integer linear programming model. In addition, the metaheuristic dominated the MILP with respect to computing time. The overall evaluation of the proposed algorithm shows its efficiency and effectiveness when compared with other algorithms. Finally, in order to obtain rigorous and fair conclusions, a paired t-test has been conducted to test the significant differences between the five variants of the TVNS_SA.

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Mathematical Modeling and Discrete Firefly Algorithm to Optimize Scheduling Problem with Release Date, Sequence-Dependent Setup Time, and Periodic Maintenance

Cited by 8 publications

References 39 publications

Modified Harmony Search Algorithm for Resource-Constrained Parallel Machine Scheduling Problem with Release Dates and Sequence-Dependent Setup Times

Modified Harmony Search Algorithm for Resource-Constrained Parallel Machine Scheduling Problem with Release Dates and Sequence-Dependent Setup Times

An Exact Method and Ant Colony Optimization for Single Machine Scheduling Problem With Time Window Periodic Maintenance

Optimize Unrelated Parallel Machines Scheduling Problems With Multiple Limited Additional Resources, Sequence-Dependent Setup Times and Release Date Constraints

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