Browsing by Subject "Metaheuristic"

Now showing 1 - 3 of 3

Open Access
Ant colony optimization for the single model U-type assembly line balancing problem
(Elsevier, 2009) Sabuncuoglu, I.; Erel, E.; Alp, A.
An assembly line is a production line in which units move continuously through a sequence of stations. The assembly line balancing problem is defined as the allocation of tasks to an ordered sequence of stations subject to precedence constraints with the objective of optimizing a performance measure. In this paper, we propose ant colony algorithms to solve the single-model U-type assembly line balancing problem. We conduct an extensive experimental study in which the performance of the proposed algorithm is compared against best known algorithms reported in the literature. The results indicate that the proposed algorithms display very competitive performance against them. © 2009 Elsevier B.V. All rights reserved.
Open Access
A local search heuristic with self-tuning parameter for permutation flow-shop scheduling problem
(IEEE, 2009) Dengiz, B.; Alabaş-Uslu, Ç.; Sabuncuoğlu, İhsan
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.
Open Access
Rural electrification: An overview of optimization methods
(Elsevier Ltd, 2021-12-23) Akbas, B.; Kocaman, Ayşe Selin; Trotter, P. A.; Nock, D.
In order to provide “affordable, reliable, sustainable and modern energy for all” by 2030 under Sustainable Development Goal 7 (SDG7), rural electrification needs significant progress as the majority of people without access to electricity reside in rural areas. Optimization methods can play a critical role in this progress, providing an analytical framework to achieve a variety of economic, social, and environmental objectives subject to budget, resources, local demographics and other constraints. This review paper presents the first overview of optimization-based solution methodologies developed or applied for rural electrification. Based on our review, we first propose four archetype problems for rural electrification, namely (i) optimal system configuration and unit sizing, (ii) optimal power dispatch strategy, (iii) optimal technology choice, and (iv) optimal network design. We discuss each problem type, and provide a systematic classification based on the problem objective, proposed solution methodology, components, scale, region as well as their relationship to the different SDG7 components. We reveal research gaps and open questions for future studies for energy researchers and aim to draw the attention of the optimization community to the challenging and unique problems that need urgent attention in this critical area.