No-wait flowshop scheduling problem with separate setup times to minimize total tardiness subject to makespan (original) (raw)
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No-wait flowshop scheduling problem with two criteria; total tardiness and makespan
European Journal of Operational Research, 2018
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Highlights No-wait flowshop scheduling problem is addressed with respect to both makespan and total tardiness An algorithm, combination of simulated annealing and insertion algorithm, is proposed Five existing algorithms are adapted to the considered problem The proposed algorithm reduces the error of the best existing algorithm (among the five algorithms adapted) about 60 %
A new heuristic for the flowshop scheduling problem to minimize makespan and maximum tardiness
International Journal of Production Research, 2009
In this paper a new heuristic for solving the flowshop scheduling problem which aims to minimising makespan and maximum tardiness is presented. The algorithm is then able to take into account the aforementioned performance measures, finding a set of non-dominated solutions representing the Pareto front. This method is based on the integration of two different techniques: a multi criteria decision making method and a constructive heuristic procedure developed for makespan minimisation in flowshop scheduling problems. In particular, the Technique for Order Preference by Similarity of Ideal Solution (TOPSIS) algorithm is integrated with the Nawaz-Enscore-Ham (NEH) heuristic to generate a set of potential scheduling solutions. To assess the proposed heuristic's performance a comparison with the best performing Multi Objective Genetic Local Search (MOGLS) algorithm proposed in literature is carried out. The test is executed on a large number of random problems characterized by different numbers of machines and jobs. The results show that the new heuristic frequently exceeds the MOGLS results in terms of both non-dominated solutions set quality and CPU time. In particular, the improvement becomes more and more significant as the number of jobs in the problem increases.
Computers & Operations Research, 2008
In this work, a review and comprehensive evaluation of heuristics and metaheuristics for the m-machine flowshop scheduling problem with the objective of minimising total tardiness is presented. Published reviews about this objective usually deal with a single machine or parallel machines and no recent methods are compared. Moreover, the existing reviews do not use the same benchmark of instances and the results are difficult to reproduce and generalise. We have implemented a total of 40 different heuristics and metaheuristics and we have analysed their performance under the same benchmark of instances in order to make a global and fair comparison. In this comparison, we study from the classical priority rules to the most recent tabu search, simulated annealing and genetic algorithms. In the evaluations we use the experimental design approach and careful statistical analyses to validate the effectiveness of the different methods tested. The results allow us to clearly identify the state-of-the-art methods.
A three-phase algorithm for flowshop scheduling with blocking to minimize makespan
Computers & Operations Research, 2012
This paper proposes a three-phase algorithm (TPA) for the flowshop scheduling problem with blocking (BFSP) to minimize makespan. In the first phase, the blocking nature of BFSP is exploited to develop a priority rule that creates a sequence of jobs. Using this as the initial sequence and a variant of the NEH-insert procedure, the second phase generates an approximate solution to the problem. Then, utilizing a modified simulated annealing algorithm incorporated with a local search procedure, the schedule generated in the second phase is improved in the third phase. A pruning procedure that helps evaluate most solutions without calculating their complete makespan values is introduced in the local search to further reduce the computational time needed to solve the problem. Results of the computational experiments with Taillard's benchmark problem instances show that the proposed TPA algorithm is relatively more effective and efficient in minimizing makespan for the BFSP than the state-of-the-art procedures. Utilizing these results, 53 out of 60 new tighter upper bounds have been found for large-sized Taillard's benchmark problem instances.
International Journal of Industrial Engineering Computations, 2022
We consider a no-wait m-machine flowshop scheduling problem which is common in different manufacturing industries such as steel, pharmaceutical, and chemical. The objective is to minimize total tardiness since it minimizes penalty costs and loss of customer goodwill. We also consider the performance measure of total completion time which is significant in environments where reducing holding cost is important. We consider both performance measures with the objective of minimizing total tardiness subject to the constraint that total completion time is bounded. Given that the problem is NP-hard, we propose an algorithm. We conduct extensive computational experiments to compare the performance of the proposed algorithm with those of three well performing benchmark algorithms in the literature. Computational results indicate that the proposed algorithm reduces the error of the best existing benchmark algorithm by 88% under the same CPU times. The results are confirmed by extensive statis...
2010
This paper presents an efficient meta-heuristic algorithm based on electromagnetism-like mechanism (EM), in which has been successfully implemented in a few combinatorial problems. We propose the EM for scheduling the flow shop problem that minimizes the makespan and total weighted tardiness and considers transportation times between machines and stage skipping (i.e., some jobs may not need to be processed on all the machines). To show the efficiency of this proposed algorithm, we also apply simulated annealing (SA) and some other well-recognized constructive heuristics, such as SPT, NEH, (g/ 2, g/2) Johnson' rule, EWDD, SLACK, and NEH_EWDD for the given problems. To evaluate the performance and robustness of our proposed EM, we experiment a number of test problems. Our computational results show that our proposed EM in almost all cases outperforms SA and other foregoing heuristics applied to this paper.
The m-machine, n-job, permutation flowshop problem with the total tardiness objective is a common scheduling problem, known to be NP-hard. Branch and bound, the usual approach to finding an optimal solution, experiences difficulty when n exceeds 20. Here, we develop a genetic algorithm, GA, which can handle problems with larger n. We also undertake a numerical study comparing GA with an optimal branch and bound algorithm, and various heuristic algorithms including the well known NEH algorithm and a local search heuristic LH. Extensive computational experiments indicate that LH is an effective heuristic and GA can produce noticeable improvements over LH.
European Journal of Operational Research, 2006
In this study, we consider the scheduling problem for two-machine flowshops with jobs of the different release times. In many real situations, jobs can be arrived at different times due to progress of jobs in the preceding stage or the status of supply of raw materials. We set the objective function of this problem to minimize the total tardiness of jobs. This job arrival constraint tends to reduce the scheduling efficiency of the production system especially in the sense of total tardiness. We developed dominance properties, lower bound and heuristics for upper bound, and adopted them to a branch-and-bound algorithm to obtain the optimal schedule for the objective of minimizing total tardiness. To test the performance of the proposed algorithm and evaluate the efficiency of the dominance properties and the lower bound, we randomly generate the problem instances and test the problem instances with the proposed algorithms. The experiment results show that CPU times are reduced by our lower bound and dominance properties.
Branch and bound algorithm for solving blocking flowshop scheduling problem with total tardiness
2013 International Conference on Control, Decision and Information Technologies (CoDIT), 2013
This paper addresses to the scheduling of a permutation flowshop scheduling problem with blocking constraints to minimize the total tardiness with a branch and bound algorithm. New machine based lower bound was developed for the problem. The experimental results have shown the efficiency of the proposed algorithm both in terms of solutions quality and time requirements.
Total tardiness minimization in permutation flowshop with deterioration consideration
Applied Mathematical Modelling, 2013
In this paper, we consider a permutation flowshop scheduling problem with deteriorating jobs. The objective is to minimize the total tardiness of all jobs. A branch-and-bound algorithm incorporating with a dominance property and a lower bound is developed. Furthermore, two metaheuristic algorithms, the simulated annealing algorithm, and the particle swarm optimization method, are proposed. Finally, computational studies are given.