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Development, application, and comparison of hybrid meta-heuristics for urban land-use allocation optimization: Tabu search, genetic, GRASP, and simulated annealing algorithms

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COMPUTERS ENVIRONMENT AND URBAN SYSTEMS 2016年第0期60卷 23-36页

作者： Mohammadi, Mahmoud Nastaran, Mahin Sahebgharani, Alireza Art Univ Isfahan Fac Architecture & Urban Planning Dept Urban Planning Esfahan Iran

Land-use optimization problem (LUOP) that seeks to allocate different land types to land units involves various dimensions and deals with numerous conflicting objectives and a large set of data and variables. Single meta heuristics are broadly developed and applied for solving LUOP. Despite the acceptable solutions derived from these algorithms, researchers in both academic and practical areas face the interesting question: can we develop an algorithm with better efficiency and solution quality? In the literature of operation research, hybridization, a combination of meta-heuristics, was introduced as a way of generating better algorithms. Therefore, this paper aims at developing novel algorithms through hybridizing Tabu search (TS), genetic algorithm (GA), GRASP, and simulated annealing (SA) and examining their quality and efficiency in practice. Accordingly, low-level teamwork GRASP-GA-TS (LLTGRGATS), high-level relay Greedy-GA-TS, and high-level teamwork SA were developed. Firstly, these algorithms were applied for solving small- and large-size single-row facility layout problem to evaluate their performance and functionality and to select the satisfactory algorithm in comparison with the other developed hybrids. Secondly, the selected algorithm, LLTGRGATS, and SVNS, a recent hybrid algorithm proposed for solving LUOP, were performed on a study area to solve a LUOP with two constraints and seven nonlinear objective functions. The outputs showed that the quality and efficiency of LLTGRGATS were slightly better than those of SVNS and it can be considered as a favorable tool for land-use planning process. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Land-use allocation Land-use optimization Hybrid meta-heuristic Population-based algorithm local search algorithm

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Evolutionary Optimization on Operating Parameters of Engine in Simulated Annealing

Evolutionary Optimization on Operating Parameters of Engine ...

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2nd International Conference on Computer and Automation Engineering (ICCAE)

作者： Xi, Pingyuan Ding, Jibin Huaihai Inst Technol Sch Mech Engn Lianyungang 222005 Peoples R China Huaihai Inst Technol Dept Mech Engn Nanjing 210046 Jiangsu Peoples R China

ISBN: (纸本)9781424455690

For a long time the design of internal combustion engine is commonly used trial and error method. By traditional design methods the design results will only be feasible option meeting the design requirements, but not be the optimal solution. Therefore it is of great significance to design the operating parameters of vehicle engine by design optimization method. The cooling area of cylinder greatly impacts on the thermal efficiency of engine, the cylinder heat loading may be measured by cooling area of unit cylinder volume, so that the smallest cylinder cooling area is chosen as the objective function. The drawbacks of the traditional optimization methods is that solving process is complicated, and optimizing process is easy to fall into local optimal solution. In this paper, the simulated annealing method is adopted to optimize operating parameters of vehicle engine, so that optimization process was simplified and the global optimal solution is ensured reliably.

关键词： operating parameters vehicle engine local search algorithm simulated annealing method

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Scheduling algorithm Based on Task Priority in Heterogeneous Computing Environment

Scheduling Algorithm Based on Task Priority in Heterogeneous...

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International Conference on Computer Science and Information Technology

作者： Yu Zhenxia Meng Fang Sheng, Shangming Chengdu Univ Informat Technol Chengdu Peoples R China Univ Elect Sci & Technol China Chengdu Peoples R China

ISBN: (纸本)9780769533087

In this paper, a scheduling algorithm suitable for independent heterogeneous tasks on heterogeneous computing has been studied. With the objective to find the best point between matching and load balancing, the concept of task priority has been used to improve the existing algorithm, and the simulation of our algorithm has been performed. The results demonstrated that through prioritizing tasks, a balance between load balancing and shortest execution time has been reached, and better scheduling performance has been achieved.

关键词： task scheduling heterogeneous computing independent task local search algorithm scheduling length

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Correction of Reference Flux for MTPA Control in Direct Torque Controlled Interior Permanent Magnet Synchronous Motor Drives

Correction of Reference Flux for MTPA Control in Direct Torq...

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International Power Electronics Conference (IPEC-ECCE-ASIA)

作者： Shinohara, Atsushi Inoue, Yukinori Morimoto, Shigeo Sanada, Masayuki Osaka Prefecture Univ Grad Sch Engn Sakai Osaka 591 Japan

ISBN: (纸本)9781479927050

This paper proposes a maximum torque per ampere control strategy for direct torque controlled interior permanent magnet synchronous motor drives. The feature of the proposed method is the ability to search the optimal current directly and successively. Therefore, variations of the parameters can be considered. The simulation and experimental results validate the proposed method.

关键词： permanent magnet synchronous motors direct torque control maximum torque per ampere control local search algorithm

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What Makes The Dynamic Capacitated Arc Routing Problem Hard To Solve: Insights From Fitness Landscape Analysis

What Makes The Dynamic Capacitated Arc Routing Problem Hard ...

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Genetic and Evolutionary Computation Conference (GECCO)

作者： Tong, Hao Minku, Leandro L. Menzel, Stefan Sendhoff, Bernhard Yao, Xin Univ Birmingham Sch Comp Sci Birmingham W Midlands England Honda Res Inst Europe Offenbach Germany SUSTech Dept Comp Sci & Engn Shenzhen Peoples R China SUSTech Res Inst Trustworthy Autonomous Syst RITAS Shenzhen Peoples R China SUSTech Guangdong Key Lab Brain Inspired Intelligent Comp Shenzhen Peoples R China

ISBN: (纸本)9781450392372

The Capacitated Arc Routing Problem (CARP) aims at assigning vehicles to serve tasks which are located at different arcs in a graph. However, the originally planned routes are easily affected by different dynamic events like newly added tasks. This gives rise to Dynamic CARP (DCARP) instances, which need to be efficiently optimized for new high-quality service plans in a short time. However, it is unknown which dynamic events make DCARP instances especially hard to solve. Therefore, in this paper, we provide an investigation of the influence of different dynamic events on DCARP instances from the perspective of fitness landscape analysis based on a recently proposed hybrid local search (HyLS) algorithm. We generate a large set of DCARP instances based on a variety of dynamic events and analyze the fitness landscape of these instances using several different measures such as fitness correlation length. From the empirical results we conclude that cost-related events have no significant impact on the difficulty of DCARP instances, but instances which require more new vehicles to serve the remaining tasks are harder to solve. These insights improve our understanding of the DCARP instances and pave the way for future work on improving the performance of DCARP algorithms.

关键词： Fitness Landscape Analysis Dynamic CARP local search algorithm Dynamic Events

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A Hybrid Particle Swarm Optimization algorithm for Combinatorial Optimization Problems

A Hybrid Particle Swarm Optimization Algorithm for Combinato...

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2010 IEEE World Congress on Computational Intelligence

作者： Rosendo, Matheus Pozo, Aurora Univ Fed Parana Dept Comp Sci BR-19081 Curitiba Parana Brazil

ISBN: (纸本)9781424481262

Particle Swarm Optimization (PSO) belongs to a class of algorithms inspired by natural social intelligent behaviors, called Swarm Intelligence (SI). PSO has been successfully applied to solve continuous optimization problems, however, its potential in discrete problems has not been sufficiently explored. Recent works have proposed hybridization of PSO using local search and Path relinking algorithms with promising results. This paper aims to present a hybrid PSO algorithm that uses local search and Path relinking too, but differently to the previous approaches, this works maintains the main PSO concept for the update of the velocity of the particle. The paper describes the proposed algorithm and a set of experiments with the Traveling Salesman Problem (TSP). The results are compared to other Particle Swarm Optimization algorithms presented previously for the same problem. The results are encouraging and reinforce the idea that PSO algorithms can also provide good results when dealing with discrete problems.

关键词： PSO TSP combinatorial optimization problem local search algorithm natural social intelligent behavior particle swarm optimisation particle swarm optimization path relinking algorithm search problems swarm intelligence traveling salesman problem travelling salesman problems

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Shrinking Hyper-Sphere based Artificial Bee Colony algorithm

Shrinking Hyper-Sphere based Artificial Bee Colony Algorithm

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IEEE International Conference on Computer, Communication and Control (IC4)

作者： Hussain, Ashik Gupta, Shruti Singh, Rohit Trivedi, Prakriti Sharma, Harish Govt Engn Coll Ajmer Ajmer India Career Point Univ Kota India Rajasthan Tech Univ Kota India

ISBN: (纸本)9781479981632

Artificial Bee Colony (ABC) is a popular swarm intelligence based approach used to solve nonlinear and complex optimization problems. It is a simple to implement and swarm based probabilistic algorithm. As the case of other swarm based algorithms, ABC is also computationally expensive due to its slow nature of search process. The solution search equation of ABC is significantly influenced by a random quantity which helps in exploration at the cost of exploitation of the search space. Therefore, to balance the exploration and exploitation characteristics of the ABC, Shrinking Hyper-Sphere based local search approach is developed and hybridized with in the ABC solution search process. The proposed algorithm is named as Shrinking Hyper-Sphere based ABC (SHABC). The experiments over 14 well known benchmark functions of complex in nature, show that the SHABC algorithm perform better than the original version of ABC and its latest variant, namely Modified ABC (MABC) in most of the experiments.

关键词： Swarm intelligence Evolutionary computation local search algorithm Shrinking Hyper-Sphere

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The research of VRP based on the improved hybrid genetic algorithm

The research of VRP based on the improved hybrid genetic alg...

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13th International Conference on Management Science and Engineering

作者： Chen Yan Hu Song-yun Qu Li-li Dalian Maritime Univ Sch Econ & Management Dalian 116026 Peoples R China

ISBN: (纸本)7560323553

The author built the mathematics model for the concluded distribution modes based on the previous domestic and international research. The stress of the paper is on how to arrange the vehicle routes of single depot and multiple customers. The paper improves the basic genetic algorithm and put forward the improved hybrid genetic algorithm which enlarges the selection solution space and combines the local search algorithm. We prove the efficiency of the improved algorithm applied in the vehicle routing problem by experiment.

关键词： distribution enlarge the selection solution space hybrid genetic algorithm local search algorithm optimization

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Enhanced Observation Scheduling Method for Space Situational Awareness 55

Enhanced Observation Scheduling Method for Space Situational...

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55th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE)

作者： Hirashima, Kazuki Watanabe, Shusuke Sawada, Megumi Ozaki, Atsuo Mitsubishi Electr Corp Informat Technol R&D Ctr Tokyo Japan

ISBN: (纸本)9784907764500

The observation scheduling method for Space Situational Awareness (SSA) that prioritizes only Observation Effectiveness (OE) has a low completion rate for user requests. In this study, we present the results from our analysis of the method of scheduling Resident Space Objects (RSO: satellites and their debris orbiting the earth) in Low Earth Orbit (LEO) that prioritizes OE and Request Completion Rate (RCR). First, we analyzed the limitations of the existing method, and then, we designed a new method that increases the RCR of the requests having a high average value of OE. The proposed method results in an improvement of 16.1% in the completion rate of high-priority requests and a reduction of only 0.063 in the average OE when compared with the corresponding results from the method that prioritizes only OE. Further, we applied a local search algorithm to improve the schedule that we created.

关键词： Space Situational Awareness Space Debris Observation Scheduling local search algorithm

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Exact Heuristic algorithm for Traveling Salesman Problem

Exact Heuristic Algorithm for Traveling Salesman Problem

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9th International Conference for Young Computer Scientists

作者： Lin, Dongmei Wu, Xiangbin Wang, Dong Foshan Univ Ctr Informat & Educ Technol Foshan 528000 Guangdong Peoples R China Cent S Univ Coll Geosci & Environm Engn Changsha 410083 Peoples R China Foshan Univ Dept Comp Sci & Technol Guanhdong PT-258000 Peoples R China

ISBN: (纸本)9781424441983

Natural properties of stochastic searching strategies and operations in metaheuristic algorithms have important influence on convergence performance of various metaheuristic algorithms. Through similarity analysis to two kinds of metaheuristic algorithms, exact heuristic algorithm based on branch-and-cut is put forward according to change trend of similarity between two arbitrary high-quality solutions. In the meanwhile, two conditions were given in this paper because efficiency of branch-and-cut algorithm is closely allied to complexity of solved object. New heuristic algorithm can help metaheuristic algorithms finding superior solutions than other heuristic algorithms, and accelerate metaheuristic algorithms convergence. Simulation experiments show that new heuristic algorithm is efficacious.

关键词： traveling salesman problem heuristic algorithm branch-and-cut exact algorithm local search algorithm

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