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Location and transportation planning in supply chains under uncertainty and congestion by using an improved electromagnetism-like algorithm

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JOURNAL OF INTELLIGENT MANUFACTURING 2018年第7期29卷 1447-1464页

作者： Fathian, Mohammad Jouzdani, Javid Heydari, Mehdi Makui, Ahmad Iran Univ Sci & Technol Sch Ind Engn POB *** Tehran Iran

Supply chain decision makers are constantly trying to improve the customer demand fulfillment process and reduce the associated costs via decision making models and techniques. As two of the most important parameters in a supply chain, supply and demand quantities are subject to uncertainty in many real-world situations. In addition, in recent decades, there is a trend to think of the impacts of supply chain design and strategies on society and environment. Especially, transportation of goods not only imposes costs to businesses but also has socioeconomic influences. In this paper, a fuzzy nonlinear programming model for supply chain design and planning under supply/demand uncertainty and traffic congestion is proposed and a hybrid meta-heuristic algorithm, based on electromagnetism-like algorithm and simulated annealing concepts, is designed to solve the model. The merit of this paper is presenting a realistic model of current issues in supply chain design and an efficient solution method to the problem. These are significant findings of this research which can be interesting to both researchers and practitioners. Several numerical examples are provided to justify the model and the proposed solution approach.

关键词： Supply chain design electromagnetism-like algorithm Demand uncertainty Supply Uncertainty Traffic congestion

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An electromagnetism-like algorithm for solving a three-dimensional highway alignment problem

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SCIENTIA IRANICA 2018年第6期25卷 2997-3020页

作者： Mohammadi, A. Poorzahedy, H. Sharif Univ Technol Dept Civil Engn Tehran Iran Sharif Univ Technol Inst Transportat Studies & Res Dept Civil Engn Tehran Iran

Road alignment design is an important determinant of the development cost of road networks. On the one side, it affects road construction and maintenance costs, constituting a significant part of country-wide infrastructure development, management, and operation budget each year. On the other side, it affects road user-related costs of travel time and vehicle use, comprising a significant portion of the total transportation cost. This study adapts the existing electromagnetism-like meta-heuristic algorithm to solve a three-dimensional highway alignment problem, which explores and finds a good route between two given points on a terrain. It detects the potentials of the given initial routes, which are enhanced and shaped to find better positions by means of local and global searches. The final good solution is, then, fine-tuned for a better alignment. Several example problems are designed to show the behavior of the algorithm. The results show that the algorithm satisfactorily maneuvers to by-pass obstacles and build highway structures where necessary. The set of the example problems in this paper may also serve to establish a basis for evaluating the performance of alternative algorithms. (C) 2018 Sharif University of Technology. All rights reserved.

关键词： Routing Three-dimensional alignment Meta-heuristic algorithm electromagnetism-like algorithm Earthwork-bridge-tunnel costs User and operator costs Reference examples

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Special Protection and Control Scheme for Transmission Line Overloading Elimination Based on Hybrid Differential Evolution/electromagnetism-like algorithm

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JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY 2017年第5期12卷 1729-1742页

作者： Hadi, Mahmood Khalid Othman, Mohammad Lutfi Wahab, Noor Izzri Abd Univ Putra Malaysia Dept Elect & Elect Engn Fac Engn Serdang Malaysia

In designing System Protection Schemes (SPSs) in power systems, protecting transmission network against extreme undesired conditions becomes a significant challenge in mitigating the transmission line overloading. This paper presents an intelligent Special Protection and Control Scheme (SPCS) using of Differential Evolution with Adaptive Mutation (DEAM) approach to obtain the optimum generation rescheduling to solve the transmission line overloading problem in system contingency conditions. DEAM algorithm employs the attraction-repulsion idea that is applied in the electromagnetism-like algorithm to support the mutation process of the conventional Differential Evolution (DE) algorithm. Different N-1 contingency conditions under base and increase load demand are considered in this paper. Simulation results have been compared with those acquired from Genetic algorithm (GA) application. Minimum severity index has been considered as the objective function. The final results show that the presented DEAM method offers better performance than GA in terms of faster convergence and less generation fuel cost. IEEE 30-bus test system has been used to prove the effectiveness and robustness of the proposed algorithm.

关键词： Special protection scheme N-1 contingency condition Transmission line overloading Generation rescheduling Differential Evolution electromagnetism-like algorithm

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A novel multi-objective approach based on improved electromagnetism-like algorithm to solve optimal power flow problem considering the detailed model of thermal generators

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INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS 2017年第4期27卷 n/a-N.PAG页

作者： Jeddi, Babak Einaddin, Alireza Hatefi Kazemzadeh, Rasool Shahid Beheshti Univ Dept Elect & Comp Engn Tehran Iran Sahand Univ Technol Fac Elect Engn Tabriz Iran

This paper formulates a new multi-objective model for the optimal power flow (OPF) problem considering 3 non-commensurable and contradictory objectives, namely cost, emission, and loss. The proposed multi-objective OPF problem takes a complete model for power generators including valve-point effects, ramp rate limits, prohibited operating zones, spinning reserve, and multi-fuel operation. Considering these constraints results in a non-convex and non-linear optimization problem and requires powerful methods to cope with. In this regard, the present paper proposes a multi-objective electromagnetism-like algorithm (EMA) based on the Pareto dominance concept and external archive strategy to solve this problem. The original EMA has poor search space exploration ability;hence, this paper proposes an improved EMA with modified local search process, which increases both exploration and intensification capabilities of the algorithm. The feasibility and effectiveness of the proposed method are tested on the IEEE 30- and 118-bus test systems and the obtained numerical results are compared with the results of the original EMA and other heuristic methods reported in the recent literature.

关键词： electromagnetism-like algorithm multi-objective optimization optimal power flow Pareto-optimality power system optimization

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Probabilistic dynamic distribution of wireless sensor networks with improved distribution method based on electromagnetism-like algorithm

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MEASUREMENT 2016年 79卷 66-76页

作者： Ozdag, Recep Karci, Ali Yuzuncu Yil UNiv Comp Sci Res & Applicat Ctr TR-65080 Van Turkey Inonu Univ Dept Comp Engn TR-44280 Malatya Turkey

Performance of the Wireless Sensor Networks (WSNs) depends significantly on coverage area which is determined via the effective dynamic distribution of sensors. Making mobile sensors' dynamic distributions, which determines their positions within the network effectively, improves performances of WSNs by enabling sensors to form the coverage area more efficiently. In this paper, we initially propose the electromagnetism-like (EM) algorithm as the sensor distribution strategy to increase the coverage area of network after random distribution of sensors. Forming more effective coverage area by using mobile and stationary sensors and probabilistic detection model has been aimed by developing the Optimal Sensor Detection algorithm that is based on the proposed EM algorithm (OSDA-EM). For this purpose, it has been thought that we would attain to more realistic results, with probabilistic detection model by forming the coverage area more effectively. Additionally, performance of the developed OSDA-EM algorithm has been compared with the Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) algorithms which was previously used in the dynamic distribution of WSNs. Simulation results have shown that the developed OSDA-EM can be preferred in dynamic distribution of WSNs that performed with probabilistic detection model. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： electromagnetism-like algorithm Wireless Sensor Networks Optimal dynamic distribution Probability detection model

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Optimal Power Flow Problem Considering the Cost, Loss, and Emission by Multi-Objective electromagnetism-like algorithm 6

Optimal Power Flow Problem Considering the Cost, Loss, and E...

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6th Conference on Thermal Power Plants (CTPP)

作者： Jeddi, Babak Einaddin, Alireza Hatefi Kazemzadeh, Rasool Shahid Beheshti Univ Elect & Comp Engn Tehran 167651719 Iran Sahand Univ Technol Tabriz Elect Distribut Co Tabriz Iran Sahand Univ Technol Fac Elect Engn Tabriz Iran

ISBN: (纸本)9781509003723

Realistic optimal power flow is a non-convex and complicated optimization problem which tries to economically dispatch the load between different generation units and some other objective functions, while the operational limitations of each unit are satisfied. In this paper three non-commensurable and contradictory objectives namely total fuel cost, total emission, and total real power loss are considered which conclude to a multi-objective (MO) optimization problem. Also, this paper proposes a multi-objective electromagnetism-like algorithm (MOEMA) based on the Pareto dominance concept and external archive strategy to solve the formulated MO problem. The feasibility and effectiveness of the proposed method is tested on the IEEE 30-bus test system and obtained numerical results are compared with the results of other heuristic methods reported in recent literature. The single and MO optimization results prove the effectiveness of the proposed optimization algorithms over other methods.

关键词： optimal power flow multi-objective optimization electromagnetism-like algorithm power system optimization

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Multi-constrained optimization in ultrasonic-assisted turning of hardened steel by electromagnetism-like algorithm

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE 2015年第11期229卷 1933-1944页

作者： Farahnakian, Masoud Razfar, Mohammad Reza Biglari, Farid Reza Amirkabir Univ Technol Dept Mech Engn Tehran 158754413 Iran

Ultrasonic-assisted machining is a method used to improve the machining technologies and overcome some problems in recent decades. To achieve optimal machining performance during hard turning, proper selection of turning parameters is considered as an important issue. The process becomes more complicated when methods such as ultrasonic-assisted machining are applied and ultrasonic vibration variables are also extracted. In this research work, a methodology is proposed to optimize ultrasonic-assisted turning process during machining of hardened steel AISI 4140. Neural network was employed to model process outputs (surface roughness and cutting force). Then electromagnetism-like algorithm was coupled to neural network to maximize the material removal rate with regard to outputs of process as constraints to achieve the machined part requirements. Experimental design technique was also used to obtain the needed experimental data for training neural network to predict process outputs. Material removal rate constitutes the main function of the electromagnetism algorithm;cutting force and surface roughness were applied as the constraints of the electromagnetism-like algorithm function. The unconstrained objective function that was created using penalty method was then optimized by the electromagnetism-like algorithm and genetic algorithm codes. It was observed that electromagnetism-like algorithm has more accurate results in comparison to genetic algorithm. Finally, the obtained optimum variables were experimentally tested in order to examine the mentioned method. Good compatibilities are observed between the values of optimization method and the experimental measurements.

关键词： electromagnetism-like algorithm constrained optimization neural network modeling ultrasonic-assisted turning design of experiments

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Improved electromagnetism-like algorithm for Nonlinear Bilevel Programming Problem 11

Improved Electromagnetism-like Algorithm for Nonlinear Bilev...

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11th International Conference on Computational Intelligence and Security (CIS)

作者： Ren, Aihong Xue, Xingsi Baoji Univ Arts & Sci Dept Math Baoji Peoples R China Fujian Univ Technol Sch Informat Sci & Engn Fuzhou Peoples R China

ISBN: (纸本)9781467386609

This paper presents an efficient hybrid heuristic search method based on electromagnetism-like algorithm and chaos searching technique to solve the nonlinear bilevel programming problem. In order to increase the population diversity, chaotic opposition-based population initialization is first applied to generate initial population. Considering the structure and characteristic of the bilevel programming problem, we introduce a simple fitness function only related to the upper level objective function. Instead of the random neighbourhood local search, chaos searching technique is used as local search. Based on these techniques, the hybrid algorithm improves the global search capability, avoids convergence to local minima and accelerates the convergence. Simulation results on test problems show that the proposed algorithm has a better performance than the compared algorithms.

关键词： Terms-Nonlinear bilevel programming problem electromagnetism-like algorithm Chaos searching technique

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A hybrid electromagnetism-like algorithm for dynamic inter/intra-cell layout problem

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INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING 2014年第6期27卷 501-518页

作者： Javadi, Babak Jolai, Fariborz Slomp, Jannes Rabbani, Masoud Tavakkoli-Moghaddam, Reza Univ Tehran Coll Engn Dept Ind Engn Tehran Iran Univ Groningen Fac Management & Org Groningen Netherlands

In this article, a new mathematical model is presented for the inter- and intra-cell layout problem under the dynamic environment. Inter/intra-cell layout is the second stage of designing a cellular manufacturing system, preceded by the cell formation stage. It involves laying out the cells in the shop floor (Inter-cell layout) and locating the machines in the cells (Intra-cell layout). The dynamic environment implies a multi-period planning horizon in which the best-designed cell layout for the current period may not be efficient for the subsequent periods and, therefore, rearrangement of the cell's layout is required. The objective is to minimise the total costs of rearrangement and inter/intra-cell material flows. An electromagnetism-like (EM-like) algorithm and a genetic algorithm (GA) are implemented to solve the proposed model. Also, a hybrid algorithm based on the EM-like algorithm and GA is proposed. Statistical tests are carried out to evaluate the performance of the algorithms using a number of numerical examples separated in the small, medium and large-sized problems. The results show the superiority of the hybrid EM-GA algorithm in comparison with other algorithms. Finally, concluding remarks are provided.

关键词： inter- and intra-cell material handling electromagnetism-like algorithm machine relocation genetic algorithm dynamic cell layout problem

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Template matching using an improved electromagnetism-like algorithm

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APPLIED INTELLIGENCE 2014年第3期41卷 791-807页

作者： Oliva, Diego Cuevas, Erik Pajares, Gonzalo Zaldivar, Daniel Univ Complutense Dept Ingn Software & Inteligencia Artificial Fac Informat E-28040 Madrid Spain Univ Guadalajara Dept Elect Guadalajara 1500 Jalisco Mexico Unidad Invest Ctr Univ Azteca Guadalajara Jalisco Mexico

Template matching (TM) plays an important role in several image-processing applications such as feature tracking, object recognition, stereo matching, and remote sensing. The TM approach seeks for the best-possible resemblance between a subimage known as template and its coincident region within a source image. TM involves two critical aspects: similarity measurement and search strategy. The simplest available TM method aims for the best-possible coincidence between the images through an exhaustive computation of the normalized cross-correlation (NCC) values (similarity measurement) for all elements of the source image (search strategy). Recently, several TM algorithms that are based on evolutionary approaches have been proposed to reduce the number of NCC operations by calculating only a subset of search locations. In this paper, a new algorithm based on the electromagnetism-like algorithm (EMO) is proposed to reduce the number of search locations in the TM process. The algorithm uses an enhanced EMO version, which incorporates a modification of the local search procedure to accelerate the exploitation process. As a result, the new EMO algorithm can substantially reduce the number of fitness function evaluations while preserving the good search capabilities of the original EMO. In the proposed approach, particles represent search locations, which move throughout the positions of the source image. The NCC coefficient, considered as the fitness value (charge extent), evaluates the matching quality presented between the template image and the coincident region of the source image, for a determined search position (particle). The number of NCC evaluations is also reduced by considering a memory, which stores the NCC values previously visited to avoid the re-evaluation of the same search locations (particles). Guided by the fitness values (NCC coefficients), the set of candidate positions are evolved through EMO operators until the best-possible resemblance is determine

关键词： Template matching electromagnetism-like algorithm Evolutionary algorithms

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