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15th International Conference on Computational Science and Its Applications (ICCSA)

作者： Soto, Ricardo Crawford, Broderick Galleguillos, Cristian Barraza, Jorge Lizama, Sebastian Munoz, Alexis Vilches, Jose Misra, Sanjay Paredes, Fernando Pontificia Univ Catolica Valparaiso Valparaiso Chile Univ Autonoma Chile Santiago Chile Univ Cient Sur Lima Peru Univ Cent Chile Santiago Chile Univ San Sebastian Santiago Chile Atilim Univ Ankara Turkey Univ Diego Portales Escuela Ingn Ind Santiago Chile

ISBN: (纸本)9783319214047;9783319214030

The set covering problem is a classical model in the subject of combinatorial optimization for service allocation, that consists in finding a set of solutions for covering a range of needs at the lowest possible cost. In this paper, we report various approximate methods to solve this problem, such as Cuckoo Search, Bee Colony, Firefly Optimization, and electromagnetism-like algorithms. We illustrate experimental results of these metaheuristics for solving a set of 65 non-unicost set covering problems from the Beasley's OR-Library.

关键词： Combinatorial optimization Set covering problem Cuckoo search algorithm Bee colony algorithm Firefly optimization algorithm electromagnetism-like algorithm

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Pre-processing, Repairing and Transfer Functions Can Help Binary electromagnetism-like algorithms 4th

Pre-processing, Repairing and Transfer Functions Can Help Bi...

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4th Computer Science On-line Conference (CSOC)

作者： Soto, Ricardo Crawford, Broderick Munoz, Alexis Johnson, Franklin Paredes, Fernando Pontificia Univ Catolica Valparaiso Valparaiso Chile Univ Autonoma Chile Santiago Chile Univ Cent Chile Santiago Chile Univ Finis Terrae Santiago Chile Univ San Sebastian Santiago Chile Univ Playa Ancha Santiago Chile Univ Diego Portales Escuela Ingn Ind Santiago Chile

ISBN: (纸本)9783319184760;9783319184753

The electromagnetism-like algorithm is a relatively modern metaheuristic based on the attraction-repulsion mechanism of particles in the context of electromagnetism theory. This paper focuses on improving performance of this metaheuristic when solving binary problems. To this end, we incorporate three elements: pre-processing, repairing, and transfers functions. The pre-processing allows to reduce the size of instances, while repairing eliminates those potential solutions that violate the constraints. Finally, the incorporation of a transfer function adapts the solutions to a binary domains. We illustrate experimental results where the incorporation of these elements improve the resolution phase, when solving a set of 65 non-unicost set covering problems.

关键词： Pre-processing Metaheuristics electromagnetism-like algorithm

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An Improved electromagnetism-like algorithm for Recurrent Neural Fuzzy Controller Design

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INTERNATIONAL JOURNAL OF FUZZY SYSTEMS 2010年第4期12卷 280-290页

作者： Lee, Ching-Hung Chang, Fu-Kai Lee, Yu-Chia Yuan Ze Univ Dept Elect Engn Tao Yuan 320 Taiwan

This paper introduces an improved electromagnetism-like algorithm (IEM) for recurrent fuzzy neural controller design. The hybrid IEM algorithm combines the advantages of the electromagnetism-like (EM) algorithm and the genetic algorithm (GA). The proposed IEM is composed of initialization, local search, total force calculation, movement, and evaluation. For recurrent fuzzy neural controller design, IEM simulates the "attraction" and "repulsion" of charged particles based on the electromagnetism theory by considering each fuzzy neural system as an electrical charge. IEM algorithm involves replacing the neighborhood randomly local search with a competitive concept and GA. IEM can treat the optimization of fuzzy neural systems for gradient information free systems. In addition, IEM has the capability of rapidly convergence and reduces the computation complexity of EM. Finally, two illustrative examples are presented to demonstrate the performance and effectiveness of IEM.

关键词： electromagnetism-like algorithm genetic algorithm fuzzy neural system nonlinear control mobile robot

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A new Hybrid electromagnetism-like algorithm for capacitated vehicle routing problems

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EXPERT SYSTEMS WITH APPLICATIONS 2010年第4期37卷 3427-3433页

作者： Yurtkuran, Alkin Emel, Erdal Uludag Univ Dept Ind Engn TR-16059 Bursa Turkey

Vehicle routing problems have been extensively analyzed within the last few decades, since they play a central role in optimization of distribution networks. This paper presents a new Hybrid electromagnetism-like algorithm for solving capacitated vehicle routing problems. electromagnetism-like algorithm is a population-based algorithm based on attraction-repulsion mechanisms between charged particles. A modified objective function value calculation approach, utilizing the Random-Key Procedure makes it possible for electromagnetism-like algorithm to solve known combinatorial optimization problems like capacitated vehicle routing problems. Here, the solutions obtained such are improved by a relatively new local search method, Iterated Swap Procedure, and tested on several benchmarking problems. The computational results show that the proposed Hybrid electromagnetism-like algorithm gives promising results within acceptable computational times when compared to other novel meta-heuristics. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： Capacitated vehicle routing problem electromagnetism-like algorithm Meta-heuristics

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A mixed-integer linear programming model along with an electromagnetism-like algorithm for scheduling job shop production system with sequence-dependent set-up times

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2010年第5-8期47卷 783-793页

作者： Roshanaei, Vahid Balagh, Akram Khaleghei Ghosheh Esfahani, Mir Mahdi Seyyed Vahdani, Behnam Amirkabir Univ Technol Tehran Polytech Dept Ind Engn Tehran Iran Univ Windsor Fac Sci Dept Math & Stat Windsor ON N9B 3P4 Canada Azad Univ Dept Ind & Mech Engn Qazvin Iran

In this paper, we consider the job shop scheduling problem (JSS) with non-anticipatory, per-machine, sequence-dependent setup times (SDST). The contributions of this paper are twofold. First, we propose a formulation in the form of a mixed-integer linear programming (MILP) model to modelize the aforementioned problem. Second, we play a pioneering effort for the effective adaptation of a novel metaheuristic known as electromagnetism-like algorithm (EMA) to solve the foregoing problem under the minimization of makespan. Afterwards, we evaluate the performance of the proposed MILP model, the EMA, and other effective metaheuristic algorithms from the literature on two different sets of benchmarks: small-sized and large-sized instances. The rationale behind applying the MILP model and the other algorithms at the small-sized instances is to compare the solutions obtained by the metaheuristic algorithms and the optimal solutions obtained by the MILP model (optimality gap analysis). Subsequently, to demonstrate the competitiveness of the EMA against some effective algorithms in the literature, we conduct an experimental design based on Taillard's benchmark, which is considered as large-sized instances. The purpose of conducting this very experiment is to show whether the acceptable performance of the EMA is transferrable to large-sized instances. The computational evaluations simply manifest the superiority of our proposed algorithm vs the other high-performing algorithms over both small and large instances.

关键词： Scheduling Job shop Mixed-integer linear programming (MILP) Sequence-dependent setup times electromagnetism-like algorithm

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Fractional-order PID controller optimization via improved electromagnetism-like algorithm

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EXPERT SYSTEMS WITH APPLICATIONS 2010年第12期37卷 8871-8878页

作者： Lee, Ching-Hung Chang, Fu-Kai Yuan Ze Univ Dept Elect Engn Tao Yuan Taiwan

Based on the electromagnetism-like algorithm, an evolutionary algorithm, improved EM algorithm with genetic algorithm technique (IEMGA), for optimization of fractional-order PID (FOPID) controller is proposed in this article. IEMGA is a population-based meta-heuristic algorithm originated from the electromagnetism theory. It does not require gradient calculations and can automatically converge at a good solution. For FOPID control optimization, IEMGA simulates the "attraction" and "repulsion" of charged particles by considering each controller parameters as an electrical charge. The neighborhood randomly local search of EM algorithm is improved by using GA and the competitive concept. IEMGA has the advantages of EM and GA in reducing the computation complexity of EM. Finally, several illustration examples are presented to show the performance and effectiveness. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： PID control Fractional-order PID control electromagnetism-like algorithm Genetic algorithm

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Research on multi-objective joint optimal flood control model for cascade reservoirs in river basin system

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NATURAL HAZARDS 2015年第3期77卷 2097-2115页

作者： Li, Qingqing Ouyang, Shuo ChangJiang Resources Commiss ChangJiang River Sci Reserch Inst Wuhan 430010 Peoples R China ChangJiang Water Resources Commiss Bur Hydrol Wuhan 430010 Peoples R China

As the large-scale cascaded reservoirs have been developed rapidly in recent years, river basin flood control (RBFC) has become a complex, multi-objective and multi-reservoir problem. In order to realize the optimal operation and management of reservoirs in mainstreams and branches, this paper presents a generalized multi-objective flood control model (MOFCM) for joint optimal dispatching of cascade reservoirs, which is applied to cascade reservoirs in lower reaches of Jinsha River and Three Gorges Reservoir in Yangtze River (JFCR-TGR). Meanwhile, a multi-objective cultural self-adaptive electromagnetism-like mechanism (MOSEM) algorithm is introduced to solve RBFC problem. In the case study, comparing with the natural runoff of the Chuan River, the maximum release of optimal schemes is lesser, its reduced range is from 1727 to 12,887 m(3)/s and the flood peak deduction rate is from 6.4 to 48 %. Results of case studies demonstrate that MOFCM is practicable and efficient for multipurpose multi-reservoir flood control. The optimal operation schemes obtained by MOSEM in JFCR-TGR system can be used to assist the decision makers in choosing the most efficient scheme. Furthermore, MOFCM can accomplish multiple-object optimization effectively under various scheduling situations.

关键词： Multi-objective optimization River basin flood control Jinsha River and Yangtze River electromagnetism-like algorithm

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Short-term multi-objective optimization scheduling for cascaded hydroelectric plants with dynamic generation flow limit based on EMA and DEA

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2014年 57卷 189-197页

作者： Wu Jiekang Guo Zhuangzhi Wu Fan Guangdong Univ Technol Sch Automat Guangzhou 510006 Guangdong Peoples R China China Three Gorges Univ Coll Sci & Technol Yichang Hubei Peoples R China

A dynamic generation flow strategy using for dynamically coordinating water head of reservoir and water consumption volume for electric energy production is presented in this paper. A novel multi-objective scheduling model is proposed to achieve the optimal trade-off between water volume for generation and electric quantity. To realize the optimal power output the coordination condition is used to describe the relationship between the current water head level and generation flow rate. The constraints are presented in an efficient method based on characters of the cascaded hydroelectric plants. A hybrid global optimization method, which can overcome the shortcoming of weighted method, is proposed for solving the multi-objective problem efficiently. This is done by embedding the data envelopment analysis (DEA) into an electromagnetism-like algorithm (EMA). A test system with eight hydroelectric plants was used to verify this new method. Results show that this novel scheduling method can enhance the synthesis generation benefit of the cascaded hydroelectric plants and realize the optimal solution for the scheduling model. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Cascaded hydroelectric plants Short term optimization scheduling Multi-objective optimization Dynamic generation flow limit electromagnetism-like algorithm Data envelopment analysis

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A Multilevel Thresholding algorithm using electromagnetism optimization

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NEUROCOMPUTING 2014年 139卷 357-381页

作者： Oliva, Diego Cuevas, Erik Pajares, Gonzalo Zaldivar, Daniel Osuna, Valentin Univ Complutense Dept Ingn Software & Inteligencia Artificial Fac Informat E-28040 Madrid Spain Univ Guadalajara CUCEI Dept Ciencias Computac Guadalajara 44430 Jalisco Mexico Ctr Invest Computac IPN Mexico City DF Mexico

Segmentation is one of the most important tasks in image processing. It consists of classifying the pixels into two or more groups depending on their intensity levels and a threshold value. The quality of the segmentation depends on the method applied to select the threshold. The use of the classical implementations for Multilevel Thresholding is computationally expensive since they exhaustively search the best values to optimize the objective function. Under such conditions, the use of optimization evolutionary approaches has been extended. The electromagnetism-like algorithm (EMO) is an evolutionary method which mimics the attraction-repulsion mechanism among charges to evolve the members of a population. Different to other algorithms, EMO exhibits interesting search capabilities whereas maintains a low computational overhead. In this paper, a Multilevel Thresholding (MT) algorithm based on the EMO is introduced. The approach combines the good search capabilities of EMO algorithm with objective functions proposed by the popular MT methods of Otsu and Kapur. The algorithm takes random samples from a feasible search space inside the image histogram. Such samples build each particle in the EMO context whereas its quality is evaluated considering the objective that is function employed by the Otsu's or Kapur's method. Guided by these objective values the set of candidate solutions are evolved through the EMO operators until an optimal solution is found. The approach generates a multilevel segmentation algorithm which can effectively identify the threshold values of a digital image in a reduced number of iterations. Experimental results show performance evidence of the implementation of EMO for digital image segmentation. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Image segmentation Evolutionary algorithms electromagnetism-like algorithm

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Train Scheduling Problem with Consideration of Praying Constraint as an Application of Job Shop Scheduling Problem

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INTERNATIONAL JOURNAL OF ENGINEERING 2014年第7期27卷 1091-1098页

作者： Jamili, A. GhannadPour, S. F. GhoreshiNejad, M. R. Univ Tehran Dept Ind Engn Tehran Iran Mapna Co Dept Railway Engn Tehran Iran

The present paper extends the idea of job shop scheduling problem with resting constraints to the train scheduling problem with the Muslim praying considerations. For this purpose, after proposing the new mathematical model, a heuristic algorithm based on the electromagnetism-like algorithm (EM) which is well adjusted to scheduling problems is employed to solve the large-size practical cases. The effectiveness of the proposed algorithm is then validated by comparing with optimum solution using small-size instances and simulated annealing algorithm, and Particle swarm Optimization (PSO) using medium and large-size instances. At the end, a practical case from Iranian railway network is studied and the results are reported. The results indicate that in the case of considering the Muslim praying constraint, the ratios of total tardiness of trains, and the total praying times are 14.5%, and 3.5%, respectively, while in the case of relaxing this constraint;the first ratio reduces to 12.3%. This result demonstrates that the proposed algorithm is able to schedule the praying times so that in many cases the trains with different directions meet each other during the praying times.

关键词： Job Shop Scheduling Train Scheduling Muslim Praying Constraint electromagnetism-like algorithm

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