An Improved Particle Swarm Optimization Algorithm Using Eagle Strategy for Power Loss Minimization

Yapıcı, Hamza; Çetinkaya, Nurettin

doi:10.1155/2017/1063045

Cited by 39 publications

(21 citation statements)

References 29 publications

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“…Although the paper shows that GM (1,1) is a flexible and easy model of use to predict what would happen in the future business and DEA is an efficient tool to help businesses find the right strategic partner, we still cannot deny some restrictions about these two methods for further studies. Different DEA models and optimization algorithm can also be tested to reveal more changes, and other industries can be studied by this model in the future [38]. This study only focuses on a quantitative model.…”

Section: Discussionmentioning

confidence: 99%

Partner Selection in Supply Chain of Vietnam’s Textile and Apparel Industry: The Application of a Hybrid DEA and GM (1,1) Approach

Wang¹,

Nguyen²,

Liao³

2017

Mathematical Problems in Engineering

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Vietnam is currently among the top-five textile and apparel exporters, and the industry is considered quite attractive to foreign investors. Nevertheless, the global textile and garment industry is experiencing important changes. The three main producing regions in the world are China, Southwest Asia (India, Pakistan, Bangladesh, and Turkey), and ASEAN. In order to maintain its positioning and to establish stable and sustainable Vietnam textile and apparel development, there must be radical changes. Due to this necessity, the authors conducted this study by using grey forecasting to predict and reflect the condition of businesses in the period of 2017-2020, together with combining a DEA model to help businesses select the most appropriate strategic partner in the supply chain in order to achieve economic goals and promote the strength of the businesses partaking in the association. Besides, this helps businesses exploit market opportunities and take advantage of the capabilities of the textile and apparel industry.

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Section: Discussionmentioning

confidence: 99%

Partner Selection in Supply Chain of Vietnam’s Textile and Apparel Industry: The Application of a Hybrid DEA and GM (1,1) Approach

Wang¹,

Nguyen²,

Liao³

2017

Mathematical Problems in Engineering

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“…For the ORPD problem, different hybridizations with PSO have been used to improve the algorithm's performance by avoiding premature convergence. For instance, PSO has been hybridized with the linear interior point method [31], fuzzy logic [32,33], Pareto optimal set [34], direct search method [35], differential evolution [36], a multi-agent systems [1], imperialist competitive algorithm [37], genetic algorithm [38] and eagle strategy [39]. Tabu search was used to solve OPF [40] and optimal reactive power planning [41] problems, but to the best of our knowledge, the hybridization of TS with PSO has never been used even though it was effective in solving other optimization-constrained problems [42].…”

Section: Proposed Hybrid Algorithmmentioning

confidence: 99%

Reactive Power Dispatch Optimization with Voltage Profile Improvement Using an Efficient Hybrid Algorithm †

et al. 2018

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This paper presents an efficient approach for solving the optimal reactive power dispatch problem. It is a non-linear constrained optimization problem where two distinct objective functions are considered. The proposed approach is based on the hybridization of the particle swarm optimization method and the tabu-search technique. This hybrid approach is used to find control variable settings (i.e., generation bus voltages, transformer taps and shunt capacitor sizes) which minimize transmission active power losses and load bus voltage deviations. To validate the proposed hybrid method, the IEEE 30-bus system is considered for 12 and 19 control variables. The obtained results are compared with those obtained by particle swarm optimization and a tabu-search without hybridization and with other evolutionary algorithms reported in the literature.

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“…Consequently, efficient metaheuristics for the models have been attracting growing attention in recent years, especially swarm intelligence metaheuristics. For example, ABC was employed to address the uncovering community problem in complex networks [42] and a novel PSO algorithm was utilized for power system optimization [43]. However, few researchers used the swarm intelligence metaheuristics to solve the problem of crosstrained worker assignment for multiple cells.…”

Section: Assignment Of Workers To Cells After Cell Formationmentioning

confidence: 99%

Cross-Trained Worker Assignment Problem in Cellular Manufacturing System Using Swarm Intelligence Metaheuristics

Cai

et al. 2018

Mathematical Problems in Engineering

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Cross-trained worker assignment has become increasingly important for manufacturing efficiency and flexibility in cellular manufacturing system because of the recent increase in labor cost. Researchers mainly focused on assigning skilled workers to tasks for favorable capacity or cost. However, few of them have recognized the need for skill level enhancement through cross-training to avoid excessive training, especially for workload balance across multiple cells. This study presents a new mathematical programming model aimed at minimum training and maximum workload balance with economical labor utilization, to address the worker assignment problem with a cross-training plan spanning multiple cells. The model considers the trade-off between training expenditure and workload balance to achieve a more flexible solution based on decision-maker’s preference. Considering the computational complexity of the problem, the classical swarm intelligence optimizers, i.e., particle swarm optimization (PSO) and artificial bee colony (ABC), are implemented to search the problem landscape. To improve the optimization performance, a superior tracking ABC with an augmented information sharing strategy is designed to address the problem. Ten benchmark problems are employed for numerical experiments. The results indicate the efficiency and effectiveness of the proposed models as well as the developed algorithms.

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An Improved Particle Swarm Optimization Algorithm Using Eagle Strategy for Power Loss Minimization

Cited by 39 publications

References 29 publications

Partner Selection in Supply Chain of Vietnam’s Textile and Apparel Industry: The Application of a Hybrid DEA and GM (1,1) Approach

Partner Selection in Supply Chain of Vietnam’s Textile and Apparel Industry: The Application of a Hybrid DEA and GM (1,1) Approach

Reactive Power Dispatch Optimization with Voltage Profile Improvement Using an Efficient Hybrid Algorithm †

Cross-Trained Worker Assignment Problem in Cellular Manufacturing System Using Swarm Intelligence Metaheuristics

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