An effective and efficient heuristic for no-wait flow shop production to minimize total completion time

Ye, Honghan; Li, Wei; Abedini, Amin; Nault, Barrie R.

doi:10.1016/j.cie.2017.04.002

Cited by 22 publications

(7 citation statements)

References 48 publications

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“…Performance indicators. Ye et al 52,53 have described the difficulty in achieving effectiveness and efficiency while finding optimized solution to no-wait flow shop scheduling problems. In this study, the performance of an algorithm is evaluated based on obtained Pareto front, called candidate PF, with the true Pareto front (PF*) to a problem.…”

Section: Solution Vector Conversionmentioning

confidence: 99%

Modeling and optimization of bakery production scheduling to minimize makespan and oven idle time

Babor

Emire

Kohlus

et al. 2023

Sci Rep

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Makespan dominates the manufacturing expenses in bakery production. The high energy consumption of ovens also has a substantial impact, which bakers may overlook. Bakers leave ovens running until the final product is baked, allowing them to consume energy even when not in use. It results in energy waste, increased manufacturing costs, and CO2 emissions. This paper investigates three manufacturing lines from small and medium-sized bakeries to find optimum makespan and ovens’ idle time (OIDT). A hybrid no-wait flow shop scheduling model considering the constraints that are most common in bakeries is proposed. To find optimal solutions, non-dominated sorting genetic algorithm (NSGA-II), strength Pareto evolutionary algorithm (SPEA2), generalized differential evolution (GDE3), improved multi-objective particle swarm optimization (OMOPSO), and speed-constrained multi-objective particle swarm optimization (SMPSO) were used. The experimental results show that the shortest makespan does not always imply the lowest OIDT. Even the optimized solutions have up to 231 min of excess OIDT, while the makespan is the shortest. Pareto solutions provide promising trade-offs between makespan and OIDT, with the best-case scenario reducing OIDT by 1348 min while increasing makespan only by 61 min from the minimum possible makespan. NSGA-II outperforms all other algorithms in obtaining a high number of good-quality solutions and a small number of poor-quality solutions, followed by SPEA2 and GDE3. In contrast, OMOPSO and SMPSO deliver the worst solutions, which become pronounced as the problem complexity grows.

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Section: Solution Vector Conversionmentioning

confidence: 99%

Modeling and optimization of bakery production scheduling to minimize makespan and oven idle time

Babor

Emire

Kohlus

et al. 2023

Sci Rep

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“…In this paper, the presented heuristic 2 (H2) is developed according to the algorithm explained by Aldowaisan and Allahverdi (2004), Ye et al (2017) and Nagano et al (2017). The novelty of creating a thorough sequence by the presented heuristic 2 (H2) consists of five parts: (1) an upper bound for the fulfillment time in order to remove job, (2) the primary sequence is to construct based on the tardiness penalty cost as well as total rejection cost, (3) NEH insertion, (4) the adjacent pairwise neighborhood exchanging, (5) a rejection job and also a rejected job insertion mechanism are used in the presented heuristic 2 (H2).…”

Section: Heuristic 2 (H2)mentioning

confidence: 99%

Modeling and solution methods for hybrid flow shop scheduling problem with job rejection

et al. 2021

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This paper addresses the hybrid flow shop scheduling problem by considering job rejection to minimize the sum of the total tardiness cost of the scheduled jobs and total cost of the rejected jobs as a single-objective problem. A mixed-integer linear programming model is proposed to solve small-sized problems within an acceptable computational time. Also, this paper exhibits two innovative heuristic algorithms, which are presented to discover fast solutions for the problem along with five meta-heuristics are adapted to solve large-sized problems in the model. Another contribution of this paper is to illustrate the different encoding and decoding methods adapted to algorithms, which are capable of obtaining a feasible schedule and furthermore, to guarantee the efficiency of the solutions based on the schedule. The results obtained from the computational study demonstrate the mathematical model and proposed algorithms effectiveness. Additionally, this paper studies the efficacy of job rejection noting the scheduling for a real-world hybrid flow shop in the tile industry production system. As well as, in this paper, the problem is viewed from a bi-objective problem perspective, so that the tardiness costs of the scheduled jobs and rejection costs of rejected jobs as two objectives are minimized simultaneously to obtain the Pareto solutions. We analyze relationship between the results of the single-objective and bi-objective approaches on small and large-sized problems.

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“…However, the new modeling technique and an enumeration algorithm are proposed to address the NWFSSP with the makespan criterion and due date constraints, which can shrink the feasible region and enhance the search speed. 5 The heuristics and constructive 1 School of Mechanical and Electrical Engineering, Henan Institute of Science and Technology, Xinxiang, China heuristics [6][7][8] are proposed to resolve the NWFSSP with makespan or total flow-time minimization criterion. In addition, to solve the NWFSSP with large size, a jigsaw puzzle-inspired algorithm is presented.…”

Section: Introductionmentioning

confidence: 99%

A discrete whale optimization algorithm for the no-wait flow shop scheduling problem

Zhang

2023

Measurement and Control

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A discrete whale optimization algorithm (DWOA) is presented to solve the no-wait flow shop scheduling problem (NWFSSP) with the optimization objective makespan. An effective combination of nearest neighbor (NN) and standard deviation heuristics (SDH) is used to acquire initial solutions of the population. After that, three crossover operators, the two-point crossover (TPX), multiple-point crossover (MPX) and job-based crossover (JBX) operators, are designed to mimics the humpback whales hunting process. Moreover, the dynamic transform mechanism of search process is designed to better balance the exploration and exploitation ability of DWOA. In order to further improve the optimization effect of DWOA, the parallel neighborhood search (PNS) and the serial neighborhood search (SNS) are selected to execute the local search and promoting global search scheme, respectively. Finally, to test the performance of DWOA, extensive experiments are conducted on benchmarks designed by Reeves and Taillard, which contain parameters tuning, effectiveness of the improvement strategies in the DWOA and comparison with several existing algorithms. From the experimental results, it is validated that the effectiveness of the improved mechanisms and the performance of the DWOA which can find better makespan values compared with other algorithms for solving NWFSSP.

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An effective and efficient heuristic for no-wait flow shop production to minimize total completion time

Cited by 22 publications

References 48 publications

Modeling and optimization of bakery production scheduling to minimize makespan and oven idle time

Modeling and optimization of bakery production scheduling to minimize makespan and oven idle time

Modeling and solution methods for hybrid flow shop scheduling problem with job rejection

A discrete whale optimization algorithm for the no-wait flow shop scheduling problem

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