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Browsing by Author "Alabas-Uslu, Cigdem"

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    A Local Search Heuristic with Self-tuning Parameter for Permutation Flow-Shop Scheduling Problem
    (2009) Dengiz, Berna; Alabas-Uslu, Cigdem; Sabuncuoglu, Ihsan
    In this paper, a new local search metaheuristic is proposed for the permutation flow-shop scheduling problem. In general, metaheuristics are widely used to solve this problem due to its NP-completeness. Although these heuristics are quite effective to solve the problem, they suffer from the need to optimize parameters. The proposed heuristic, named STLS, has a single self-tuning parameter which is calculated and updated dynamically based on both the response surface information of the problem field and the performance measure of the method throughout the search process. Especially, application simplicity of the algorithm is attractive for the users. Results of the experimental study show that STLS generates high quality solutions and outperforms the basic tabu search, simulated annealing, and record-to-record travel algorithms which are well-known local search based metaheuristics.
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    Parameter Tuning Problem in Metaheuristics: A Self-Adaptive Local Search Algorithm for Combinatorial Problems
    (2020) Alabas-Uslu, Cigdem; Dengiz, Berna
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    A Self-adaptive Local Search Algorithm for the Classical Vehicle Routing Problem
    (2011) Alabas-Uslu, Cigdem; Dengiz, Berna
    The purpose of this study is introduction of a local search heuristic free from parameter tuning to solve classical vehicle routing problem (VRP). The VRP can be described as the problem of designing optimal delivery of routes from one depot to a number of customers under the limitations of side constraints to minimize the total traveling cost. The importance of this problem comes from practical as well as theoretical point of view. The proposed heuristic, self-adaptive local search (SALS), has one generic parameter which is learnt throughout the search process. Computational experiments confirm that SALS gives high qualified solutions to the VRP and ensures at least an average performance, in terms of efficiency and effectiveness, on the problem when compared with the recent and sophisticated approaches from the literature. The most important advantage of the proposed heuristic is the application convenience for the end-users. SALS also is flexible that can be easily applied to variations of VRP. (C) 2011 Elsevier Ltd. All rights reserved.
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    A Self-tuning Heuristic for the Design of Communication Networks
    (2015) Dengiz, Berna; Alabas-Uslu, Cigdem
    This paper addresses the design of communication networks that has a large application area. The problem is to design a minimum cost network subject to a given reliability level. Complexity of the problem is twofold: (1) finding a minimum-cost network topology that every pair of nodes can communicate with each other and (2) computing overall reliability to provide the reliability constraint. Over the last two decades, metahemistic algorithms have been widely applied to solve this problem due to its NP-hardness. In this study, a self-tuning heuristic (STH), which is a new approach free from parameter tuning, is applied to the design of communication networks. Extensive computational results confirm that STH generates superior solutions to the problem in comparison to some well-known local search metaheuristics, and also more sophisticated metaheuristics proposed in the literature. The practical advantage of STH lies in both its effectiveness and simplicity in application to the design problem.

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