Multi objective lotsizing and scheduling with material constraints in flexible parallel lines using a Pareto based guided artificial bee colony algorithm

Yue, Lei; Guan, Zailin; Zhang, Li; Ullah, Saif; Cui, Yanyan

doi:10.1016/j.cie.2018.12.065

Cited by 26 publications

(19 citation statements)

References 48 publications

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“…Therefore, lotsizing and mixed model sequencing problema have significant application in manufacturing industries. Lotsizing and scheduling problems have been well studied in the literature [5][6][7][8]. The literature, divides lotsizing problems into two categories, including single level systems and multi-level systems [9,10].…”

Section: Dynamic Lotsizing and Scheduling On Multiple Linesmentioning

confidence: 99%

“…In most manufacturing industries, products are made in multiple stages and therefore, the lotsizing and mixed model sequencing problem in a multi-stage production environment is the focus of the current study. In the literature, multi-level lotsizing problem have been studied by several researchers for different production environment [5,8,10,[12][13][14][15]. Karimi [10] studied the multi-level lotsizing and scheduling problem in a job shop environment.…”

Section: Dynamic Lotsizing and Scheduling On Multiple Linesmentioning

confidence: 99%

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Dynamic Mixed Model Lotsizing and Scheduling for Flexible Machining Lines Using a Constructive Heuristic

et al. 2021

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Dynamic lotsizing and scheduling on multiple lines to meet the customer due dates is significant in multi-line production environments. Therefore, this study investigates dynamic lotsizing and scheduling problems in multiple flexible machining lines considering mixed products. In addition, uncertainty in demand and machine failure is considered. A mathematical model is proposed for the considered problem with an aim to maximize the probability of completion of product models from different customer orders. A constructive heuristic method (CHLP) is proposed to solve the current problem. The proposed heuristic involves the steps to distribute different customer order demands among multiple lines and schedule them considering balancing of makespan between the lines. The performance of CHLP is measured with famous heuristics from the literature, based on the test problem instances. Results indicate that CHLP gives better results in terms of quality of results as compared to other famous literature heuristics.

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Section: Dynamic Lotsizing and Scheduling On Multiple Linesmentioning

confidence: 99%

Section: Dynamic Lotsizing and Scheduling On Multiple Linesmentioning

confidence: 99%

Dynamic Mixed Model Lotsizing and Scheduling for Flexible Machining Lines Using a Constructive Heuristic

et al. 2021

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“…As single projects are combined with multiple projects, so release date and resource capacities are specified. Since these instances did not have any cost date, so the cost assignment technique is adopted from Yue et al [49]. The characteristics of the cases are given in Table 1.…”

Section: A Test Casesmentioning

confidence: 99%

“…Alongside these algorithms, several researchers [14], [23], [25], [46] have also proposed hybrid algorithms to enhance their performance. Beside these algorithms; algorithms based on the social structure and food searching behavior of animals known as swarm intelligent optimization algorithms tends to perform well for continuous as well as constrained optimization problem [47]- [49]. Therefore, in this research, raccoon family optimization (RFO) algorithm is proposed which mimic the social structure and foraging behaviour of raccoons.…”

Section: Introductionmentioning

confidence: 99%

Integrated Planning and Scheduling of Multiple Manufacturing Projects Under Resource Constraints Using Raccoon Family Optimization Algorithm

et al. 2020

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Today's dynamic environment and increasing demand for highly customized products have significantly increased the number of companies operating in the project environment. Project planning and scheduling are one of the major problems faced by managers due to resource constraints. Enterprises have to execute several projects simultaneously while sharing limited resources (i.e., human resources, equipment, and budget) among the projects to effectively meet the deadlines. Therefore, this work investigates the integrated planning and scheduling problem of multiple projects with different release dates and execution modes while considering the renewable and non-renewable resource constraints. Moreover, the raccoon family optimization (RFO) algorithm is proposed to maximize the net profit while considering the early completion bonus, penalty cost, and resource costs. In the proposed RFO algorithm, greedy search and modified genetic operators are introduced to enhance the performance and efficiency. Effectiveness of the proposed RFO algorithm is compared with the genetic algorithm (GA), raccoon optimization algorithm (ROA), and artificial bee colonial (ABC) algorithm on test cases as well as an industrial case study. The results indicate that the proposed RFO algorithm outperforms the other compared algorithms, both in terms of effectiveness and efficiency. INDEX TERMS Project planning and scheduling, multiple projects, resource constraint, execution modes, Raccoon family optimization algorithm.

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“…To further evaluate the performance of the proposed HGTS algorithm, the results obtained by HGTS are compared with the best solutions for each instance. Regarding the nonlinearity of the proposed model, the approximate optimal solutions can be obtained by all the compared algorithms running for large number of cycles [52], [53]. The performance of all algorithms is evaluated based on different indicators including quality of solutions and convergence.…”

Section: Comparison Among Algorithmsmentioning

confidence: 99%

The Printed-Circuit-Board Electroplating Parallel-Tank Scheduling With Hoist and Group Constraints Using a Hybrid Guided Tabu Search Algorithm

et al. 2019

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Current research investigates a parallel-tank scheduling problem with hoist and group constraints in printed-circuit-board (PCB) electroplating environment, where the hoist is used as a material handling device and PCBs need to be grouped for further processing. The purpose of the current research is to minimize the makespan and total weighted tardiness of PCB products. The weighted ideal point method is used to combine these two objectives into a single optimization objective. Moreover, a mixed integer programming model is developed to formulate the problem. Since the problem is proved to be NP-hard, a hybrid guided tabu search (HGTS) algorithm is proposed to optimize the objectives. A heuristic method based on small combination sequences called SCS is applied to search the better initial solution. Moreover, a problem-oriented guided neighborhood move strategy is adopted to improve the search efficiency in the proposed HGTS algorithm. The experiments are conducted on different size of problem instances. The performance of the proposed HGTS algorithm is investigated and compared with other existing algorithms. The detailed results indicate that the proposed HGTS algorithm performs better both in objective value and convergence speed. Finally, a real-world case is solved by the proposed HGTS, which validates that the proposed algorithm is effective and useful in solving the practical electroplating scheduling problem. INDEX TERMS Hoist and group constraints, hybrid guided tabu search, parallel-tank scheduling, small combination sequences, weighted ideal point method.

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Multi objective lotsizing and scheduling with material constraints in flexible parallel lines using a Pareto based guided artificial bee colony algorithm

Cited by 26 publications

References 48 publications

Dynamic Mixed Model Lotsizing and Scheduling for Flexible Machining Lines Using a Constructive Heuristic

Dynamic Mixed Model Lotsizing and Scheduling for Flexible Machining Lines Using a Constructive Heuristic

Integrated Planning and Scheduling of Multiple Manufacturing Projects Under Resource Constraints Using Raccoon Family Optimization Algorithm

The Printed-Circuit-Board Electroplating Parallel-Tank Scheduling With Hoist and Group Constraints Using a Hybrid Guided Tabu Search Algorithm

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