Fixed Set Search Applied to the Minimum Weighted Vertex Cover Problem

Jovanović, Raka; Voß, Stefan

doi:10.1007/978-3-030-34029-2_31

Cited by 13 publications

(4 citation statements)

References 16 publications

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“…An example is the fixed set search of Jovanovic et al. (2019) superimposed on the GRASP. Another idea that could be subsumed under this category, though developed in a different context, is target analysis as described, for example, in Laguna and Glover (1993).…”

Section: Learningmentioning

confidence: 99%

“…It is of interest that the pilot method also, to a large extent, relies on repetition; see Duin and Voß (1999). GRASP was by design used in the initialization of the recently proposed fixed set search metaheuristic (Jovanovic et al., 2019), which has shown favorable results in quite a few problems (e.g., Jovanovic and Voß, 2021).…”

Section: Constrained Optimizationmentioning

confidence: 99%

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Initialization of metaheuristics: comprehensive review, critical analysis, and research directions

Sarhani

Voß

Jovanović

2022

Int Trans Operational Res

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Initialization of metaheuristics is a crucial topic that lacks a comprehensive and systematic review of the state of the art. Providing such a review requires in‐depth study and knowledge of the advances and challenges in the broader field of metaheuristics, especially with regard to diversification strategies, in order to assess the proposed methods and provide insights for initialization. Motivated by the aforementioned research gap, we provide a related review and begin by describing the main metaheuristic methods and their diversification mechanisms. Then, we review and analyze the existing initialization approaches while proposing a new categorization of them. Next, we focus on challenging optimization problems, namely constrained and discrete optimization. Lastly, we give insights on the initialization of local search approaches.

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Section: Learningmentioning

confidence: 99%

Section: Constrained Optimizationmentioning

confidence: 99%

Initialization of metaheuristics: comprehensive review, critical analysis, and research directions

Sarhani

Voß

Jovanović

2022

Int Trans Operational Res

Self Cite

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“…To further enhance the search ability, the local search strategy is always embedded into various intelligence algorithms [36,37]. Here, the local search strategy starts from a given solution and stops when the predefined maximum number of iterations is met.…”

Section: Local Search Strategymentioning

confidence: 99%

Modified Migrating Birds Optimization for Energy-Aware Flexible Job Shop Scheduling Problem

Zhu

Jiang

2020

Algorithms

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In recent decades, workshop scheduling has excessively focused on time-related indicators, while ignoring environmental metrics. With the advent of sustainable manufacturing, the energy-aware scheduling problem has been attracting more and more attention from scholars and researchers. In this study, we investigate an energy-aware flexible job shop scheduling problem to reduce the total energy consumption in the workshop. For the considered problem, the energy consumption model is first built to formulate the energy consumption, such as processing energy consumption, idle energy consumption, setup energy consumption and common energy consumption. Then, a mathematical model is established with the criterion to minimize the total energy consumption. Secondly, a modified migrating birds optimization (MMBO) algorithm is proposed to solve the model. In the proposed MMBO, a population initialization scheme is presented to ensure the initial solutions with a certain quality and diversity. Five neighborhood structures are employed to create neighborhood solutions according to the characteristics of the problem. Furthermore, both a local search method and an aging-based re-initialization mechanism are developed to avoid premature convergence. Finally, the experimental results validate that the proposed algorithm is effective for the problem under study.

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“…Recently, a new metaheuristic called the fixed set search (FSS) has been developed which, in a simple way, adds a learning mechanism to GRASP (Jovanovic, Tuba, & Voß, 2019). The FSS has been successfully applied to the travelling salesmen problem (TSP; Jovanovic et al, 2019) and the minimum weighted vertex cover problem (Jovanovic & Voß, 2019). In this article, the FSS algorithm, based on the developed GRASP, is applied to the PDSP and its connected version.…”

Section: Introductionmentioning

confidence: 99%

The fixed set search applied to the power dominating set problem

Jovanović

Voß

2020

Expert Systems

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In this article, we focus on solving the power dominating set problem and its connected version. These problems are frequently used for finding optimal placements of phasor measurement units in power systems. We present an improved integer linear program (ILP) for both problems. In addition, a greedy constructive algorithm and a local search are developed. A greedy randomised adaptive search procedure (GRASP) algorithm is created to find near optimal solutions for large scale problem instances. The performance of the GRASP is further enhanced by extending it to the novel fixed set search (FSS) metaheuristic. Our computational results show that the proposed ILP has a significantly lower computational cost than existing ILPs for both versions of the problem. The proposed FSS algorithm manages to find all the optimal solutions that have been acquired using the ILP. In the last group of tests, it is shown that the FSS can significantly outperform the GRASP in both solution quality and computational cost.

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Fixed Set Search Applied to the Minimum Weighted Vertex Cover Problem

Cited by 13 publications

References 16 publications

Initialization of metaheuristics: comprehensive review, critical analysis, and research directions

Initialization of metaheuristics: comprehensive review, critical analysis, and research directions

Modified Migrating Birds Optimization for Energy-Aware Flexible Job Shop Scheduling Problem

The fixed set search applied to the power dominating set problem

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