Solving the Open Shop Scheduling Problem via a Hybrid Genetic-Variable Neighborhood Search Algorithm

Zobolas, G. I.; Tarantilis, Christos D.; Ioannou, George

doi:10.1080/01969720902830322

Cited by 13 publications

(5 citation statements)

References 31 publications

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“…This feedback mechanism ensures the algorithm's robustness and reliability, thereby enhancing solution-finding efficiency. To generate neighborhood solutions, this paper employs the 2 − opt operator [29]. As depicted in Figure 7, this operator constructs new feasible solutions by eliminating two edges from the original feasible solution and subsequently reintroducing two edges.…”

Section: Attack Operatormentioning

confidence: 99%

Solving the Vehicle Routing Problem with Time Windows Using Modified Rat Swarm Optimization Algorithm Based on Large Neighborhood Search

Wei,

Xiao,

Wang

2024

Mathematics

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The vehicle routing problem with time windows (VRPTW) remains a formidable challenge, due to the intricate constraints of vehicle capacity and time windows. As a result, an algorithm tailored for this problem must demonstrate robust search capabilities and profound exploration abilities. Traditional methods often struggle to balance global search capabilities with computational efficiency, thus limiting their practical applicability. To address these limitations, this paper introduces a novel hybrid algorithm known as large neighborhood search with modified rat swarm optimization (LNS-MRSO). Modified rat swarm optimization (MRSO) is inspired by the foraging behavior of rat swarms and simulates the search process for optimization problems. Meanwhile, large neighborhood search (LNS) generates potential new solutions by removing and reinserting operators, incorporating a mechanism to embrace suboptimal solutions and strengthening the algorithm’s prowess in global optimization. Initial solutions are greedily generated, and five operators are devised to mimic the position updates of the rat swarm, providing rich population feedback to LNS and further enhancing algorithm performance. To validate the effectiveness of LNS-MRSO, experiments were conducted using the Solomon VRPTW benchmark test set. The results unequivocally demonstrate that LNS-MRSO achieves optimal solutions for all 39 test instances, particularly excelling on the R2 and RC2 datasets with percentage deviations improved by 5.1% and 8.8%, respectively, when compared to the best-known solutions (BKSs). Furthermore, when compared to state-of-the-art algorithms, LNS-MRSO exhibits remarkable advantages in addressing VRPTW problems with high loading capacities and lenient time windows. Additionally, applying LNS-MRSO to an unmanned concrete-mixing station further validates its practical utility and scalability.

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Section: Attack Operatormentioning

confidence: 99%

Solving the Vehicle Routing Problem with Time Windows Using Modified Rat Swarm Optimization Algorithm Based on Large Neighborhood Search

Wei,

Xiao,

Wang

2024

Mathematics

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“…Sha and Hsu (2008) introduced a particle swarm optimization algorithm for the OSSP that obtained many new best-known solutions of benchmark problems (Taillard, 1993; Bruckner et al , 1997; Guéret and Prins, 1999). Zobolas et al (2009) proposed a hybrid metaheuristic for the OSSP and applied it to benchmark instances, as well as a proposed a set of instances based on industrial cases. Rahmani Hosseinabadi et al (2018) proposed a genetic algorithm for the OSSP, which could find more optimal solutions in shorter computational times compared to other algorithms in the literature.…”

Section: Related Workmentioning

confidence: 99%

Modeling and scheduling hybrid open shops for makespan minimization

Araújo

Bonates

Prata

2021

JM2

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Purpose This study aims to address the hybrid open shop problem (HOSP) with respect to the minimization of the overall finishing time or makespan. In the HOSP, we have to process n jobs in stages without preemption. Each job must be processed once in every stage, there is a set of mk identical machines in stage k and the production flow is immaterial. Design/methodology/approach Computational experiments carried out on a set of randomly generated instances showed that the minimal idleness heuristic (MIH) priority rule outperforms the longest processing time (LPT) rule proposed in the literature and the other proposed constructive methods on most instances. Findings The proposed mathematical model outperformed the existing model in the literature with respect to computing time, for small-sized instances, and solution quality within a time limit, for medium- and large-sized instances. The authors’ hybrid iterated local search (ILS) improved the solutions of the MIH rule, drastically outperforming the models on large-sized instances with respect to solution quality. Originality/value The authors formalize the HOSP, as well as argue its NP-hardness, and propose a mixed integer linear programming model to solve it. The authors propose several priority rules – constructive heuristics based on priority measures – for finding feasible solutions for the problem, consisting of adaptations of classical priority rules for scheduling problems. The authors also propose a hybrid ILS for improving the priority rules solutions.

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“…Zobolas et al [57] developed a hybrid genetic algorithm that solves the open shop scheduling problem to minimize the makespan. In the first phase, they developed a variable neighborhood search (VNS) algorithm in which the initial population is generated using NEH heuristic (Nawaz-Enscore-Ham Heuristic).…”

Section: Genetic Algorithmsmentioning

confidence: 99%

Literature Review of Open Shop Scheduling Problems

Anand¹,

Panneerselvam²

2015

IIM

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This paper discusses review of literature of open shop scheduling problems. First, the problem is classified as per different measures of performance, viz., minimization of makespan, minimization of sum of completion times of jobs, minimization of sum of weighted completion times of all jobs, minimization of total tardiness of all jobs, minimization of sum of weighted tardiness of all jobs, minimization of weighted sum of tardy jobs, and miscellaneous measures of the open shop scheduling problem. In each category, the literature is further classified based on approaches used and then the contributions of researchers in the respective categories are presented. Directions for future research are discussed in the end.

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Solving the Open Shop Scheduling Problem via a Hybrid Genetic-Variable Neighborhood Search Algorithm

Cited by 13 publications

References 31 publications

Solving the Vehicle Routing Problem with Time Windows Using Modified Rat Swarm Optimization Algorithm Based on Large Neighborhood Search

Solving the Vehicle Routing Problem with Time Windows Using Modified Rat Swarm Optimization Algorithm Based on Large Neighborhood Search

Modeling and scheduling hybrid open shops for makespan minimization

Literature Review of Open Shop Scheduling Problems

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