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A hybrid electromagnetism algorithm for multi-depot periodic vehicle routing problem

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2014年第1-4期71卷 509-518页

作者： Mirabi, Mohammad Ayatollah Haeri Univ Meybod Grp Ind Engn Meybod Iran

electromagnetism algorithm is a meta-heuristic proposed to derive approximate solutions for computationally hard problems. In the literature, several successful applications have been reported for graph-based optimization problems, such as scheduling problems. This paper presents a novel hybrid electromagnetism algorithm called SA_EM to solve the multi-depot periodic vehicle routing problem (MDPVRP). The main feature of the hybrid algorithm is to hybridize the solution construction mechanism of the electromagnetism (EM) with simulated annealing (SA). Moreover, during implementing the hybrid algorithm, cyclic transfers, an effective class of neighborhood search is applied. The objective consists of two terms as follows: total traveled distance at each depot and total waiting time of all customers to take service. Distances are assumed Euclidean or straight line. These conditions are exactly consistent with the real-world situation and have little attention in the literature. Finally, the experimental results have shown that the proposed hybrid method is competitive to solve the vehicle routing problem compared with the best existing methods in terms of solution quality.

关键词： Periodic vehicle routing problem Multi-depot electromagnetism algorithm Simulated annealing

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A multi-objective electromagnetism algorithm for a bi-objective flowshop scheduling problem

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JOURNAL OF MANUFACTURING SYSTEMS 2012年第2期31卷 232-239页

作者： Khalili, Majid Tavakkoli-Moghaddam, Reza Islamic Azad Univ Sci & Res Branch Dept Ind Engn Tehran Iran Univ Tehran Dept Ind Engn Coll Engn Tehran Iran

This paper deals with a bi-objective flowshop scheduling problem minimizing the makespan and total weighted tardiness, in which all jobs may not be processed by all machines. Furthermore, we consider transportation times between machines. Obtaining an optimal solution for this type of complex, large-sized problem in reasonable computational time by using traditional approaches and optimization tools is extremely difficult. This paper presents a new multi-objective electromagnetism algorithm (MOEM). The motivation behind this algorithm has risen from the attraction repulsion mechanism of electromagnetic theories. Along with MOEA, we apply simulated annealing to solve the given problem. A set of experimental instances are carried out to evaluate the algorithm by advanced multi-objective performance measures. The related results show that a variant of our proposed MOEM provides sound performance comparing with other algorithms. (C) 2011 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.

关键词： electromagnetism algorithm Bi-objective flowshop scheduling Makespan Total weighted tardiness Transportation times

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Memetic electromagnetism algorithm for surface reconstruction with rational bivariate Bernstein basis functions

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NATURAL COMPUTING 2017年第4期16卷 511-525页

作者： Iglesias, Andres Galvez, Akemi Univ Cantabria Dept Appl Math & Computat Sci ETSI Caminos Canales & Puertos Avda Castros S-N E-39005 Santander Spain Toho Univ Dept Informat Sci Fac Sci Narashino Campus2-2-1 Miyama Funabashi Chiba 2748510 Japan

Surface reconstruction is a very important issue with outstanding applications in fields such as medical imaging (computer tomography, magnetic resonance), biomedical engineering (customized prosthesis and medical implants), computer-aided design and manufacturing (reverse engineering for the automotive, aerospace and shipbuilding industries), rapid prototyping (scale models of physical parts from CAD data), computer animation and film industry (motion capture, character modeling), archaeology (digital representation and storage of archaeological sites and assets), virtual/augmented reality, and many others. In this paper we address the surface reconstruction problem by using rational B,zier surfaces. This problem is by far more complex than the case for curves we solved in a previous paper. In addition, we deal with data points subjected to measurement noise and irregular sampling, replicating the usual conditions of real-world applications. Our method is based on a memetic approach combining a powerful metaheuristic method for global optimization (the electromagnetism algorithm) with a local search method. This method is applied to a benchmark of five illustrative examples exhibiting challenging features. Our experimental results show that the method performs very well, and it can recover the underlying shape of surfaces with very good accuracy.

关键词： Surface reconstruction Rational surfaces Memetic approach electromagnetism algorithm Local search

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Improving electromagnetism algorithm for solving resource allocation problem in stochastic networks

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COMPUTERS & OPERATIONS RESEARCH 2017年 86卷 30-40页

作者： Chu, Weng-Ming Chang, Koan-Yuh Natl Chin Yi Univ Technol Dept Elect Engn Taichung Taiwan Chien Kuo Technol Univ Dept Elect Engn Changhua Changhua County Taiwan

This study investigates optimal resource allocation for minimizing total cost in stochastic networks (SN) where the duration of all activities involved is not only a random variable, but also a function of the resources allocated. The total cost of the network comprises resource usage cost and penalty cost. An electromagnetism algorithm (EA) is used as a decision tool for optimization and a Label-Correcting Tracing algorithm (LCTA) for approximation of completion time in SN is suggested. Furthermore, the Critical Path Cluster algorithm (CPCA) and Cluster Local Search algorithm (CLSA) are developed to enhance EA's search ability for resource allocation. Results from numerical experiments show that the proposed EA yields good solution quality. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Heuristic electromagnetism algorithm Networks Optimal resource allocation

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Modeling and scheduling a case of flexible flowshops: Total weighted tardiness minimization

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COMPUTERS & INDUSTRIAL ENGINEERING 2009年第4期57卷 1258-1267页

作者： Naderi, B. Zandieh, M. Shirazi, M. A. H. A. Shahid Beheshti Univ Management & Accounting Fac Dept Ind Management GC Tehran Iran Amirkabir Univ Technol Dept Ind Engn Tehran Iran

Two of the most realistic assumptions in the field of scheduling are the consideration of setup and transportation times. In this paper, we study the flexible flowshop scheduling where setup times are anticipatory sequence-dependent and transportation times are job-independent. We also assume that there are several transporters to carry jobs. The objective is to minimize total weighted tardiness. We first formulate the problem as a mixed integer linear programming (MILP) model. With this, we solve small-sized instances to optimality. Since this problem is known to be NP-hard, we then propose an effective metaheuristic to tackle large-sized instances. This metaheuristic, called electromagnetism algorithm (EMA), originates from the attraction-repulsion mechanism of the electromagnetism theory. We conduct a series of experiments and complete statistical analyses to evaluate the performance of the proposed MILP model and EMA. On a set of instances, we first tune the parameters of EMA. Then, the efficiency of the model and general performance of the proposed EMA are assessed over a set of small-sized instances. To further evaluate EMA, we compare it against two high performing metaheuristics;existing in the literature over a set of large-sized instances. The results demonstrate that the proposed MILP model and EMA are effective for this problem. (C) 2009 Published by Elsevier Ltd.

关键词： Flexible flowshop Total weighted tardiness Anticipatory sequence-dependent setup times Transportation times Mixed integer linear program electromagnetism algorithm

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A novel hybrid column generation-metaheuristic approach for the vehicle routing problem with general soft time window

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INFORMATION SCIENCES 2015年 316卷 598-615页

作者： Beheshti, Ali Kourank Hejazi, Seyed Reza Isfahan Univ Technol Dept Ind & Syst Engn Esfahan 841568311 Iran

The vehicle routing problem with general soft time window involves designing a set of routes for a fleet of vehicles based at a central depot that is required to service a number of geographically dispersed customers while minimizing the total travel distance and delivery time costs. Delivery time cost function is a general piecewise linear function. In this study, we propose a mathematical model of this problem. Then an efficient hybrid column generation-metaheuristic approach is developed. In the proposed algorithm, the hybridization of column generation (CG) and the metaheuristic is performed in both integrative and collaborative modes. In the integrative phase, a quantum-inspired evolutionary algorithm is used to solve the sub-problems of column generation. In the collaborative phase, the column generation and electromagnetism algorithms are parallelized, and the information from these two algorithms is exchanged to find better solutions. Finally, the performance of the proposed approach is evaluated using a set of modified classic benchmark instances adopted from the literature. (C) 2014 Elsevier Inc. All rights reserved.

关键词： Column generation heuristic Vehicle routing problem with general soft time window Quantum-inspired evolutionary algorithm electromagnetism algorithm

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An electromagnetism-like metaheuristic for open-shop problems with no buffer

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Journal of Industrial Engineering International 2012年第1期8卷 1-8页

作者： Naderi, Bahman Najafi, Esmaeil Yazdani, Mehdi Department of Industrial Engineering Faculty of Engineering University of Kharazmi Karaj Iran Department of Industrial Engineering Science & Research Branch Islamic Azad University Tehran Iran Department of Industrial Engineering Qazvin Branch Islamic Azad University Qazvin Iran

This paper considers open-shop scheduling with no intermediate buffer to minimize total tardiness. This problem occurs in many production settings, in the plastic molding, chemical, and food processing industries. The paper mathematically formulates the problem by a mixed integer linear program. The problem can be optimally solved by the model. The paper also develops a novel metaheuristic based on an electromagnetism algorithm to solve the large-sized problems. The paper conducts two computational experiments. The first includes small-sized instances by which the mathematical model and general performance of the proposed metaheuristic are evaluated. The second evaluates the metaheuristic for its performance to solve some large-sized instances. The results show that the model and algorithm are effective to deal with the problem. © 2012, Naderi et al.;licensee Springer.

关键词： electromagnetism algorithm Mixed integer linear programming Open shop with no buffer Scheduling

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