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Application of tabu search Heuristic algorithms for the Purpose of Energy Saving in Optimal Load Distribution Strategy for Multiple Chiller Water Units

Application of Tabu Search Heuristic Algorithms for the Purp...

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The 2010 IEEE International Conference on Progress in Informatics and Computing

作者： Jun Zhang School of Mechatronics Engineering and Automation Shanghai University Shanghai,China,200072 Kanyu Zhang School of Mechatronics Engineering and Automation Shanghai University Shanghai,China,200072

tabu search algorithm has been applied to solve the optimal load distribution strategy problem for the cooling system constituted by multiple chiller water units,which has the characteristic such as complexity,constraint,nonlinearity, modeling difficulty,*** tabu search algorithms based on the neighborhood search can avoid the local optimization avoidance and has the artificial intelligence memory *** this paper,two chiller water units connected in parallel working using the tabu algorithm was *** with the conventional method,the results indicated that the tabu search algorithms has much less power consumption and is very suitable for application in air condition system operation.

关键词： energy consumption energy saving algorithm tabu search algorithms optimal chiller load distribution part load chiller water units direct load control

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Identification of Axial Compressor Dynamics using tabu search Optimization

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IFAC-PapersOnLine 2015年第28期48卷 1160-1165页

作者： Schoen, Marco P. Lee, Ji-Chao Lin, Feng Idaho State University PocatelloID83209 United States Chinese Academy of Science Institute of Engineering Thermophysics Beijing China

Identification of a one stage axial compressor system is addressed using existing and a newly proposed approach that incorporates a priori knowledge of the system into the identification algorithm. The optimization of the proposed cost functions is accomplished by utilizing a tabu search algorithm. In addition to the identification of the compressor dynamics, a new measure for the flow state in the blade passage is proposed. The identification of the dynamics within the blade passage and the proposed flow measure allow for the inspection of the limits for the utilized actuation. © 2015

关键词： Compressors Axial flow turbomachinery Cost functions Dynamics tabu search Axial compressors Eigensystem Identification algorithms Intelligent optimization Priori knowledge search optimization Spectral entropy tabu search algorithms

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A developed tabu search algorithm for heterogeneous fleet vehicle routing problem

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IFAC-PapersOnLine 2019年第13期52卷 1051-1056页

作者： Meliani, Youssef Hani, Yasmina Elhaq, Sâad Lissane El Mhamedi, Abderrahman University of Hassan II ENSEM Casablanca Morocco Equipe Optimisation des systèmes de production et énergie France University of Paris 8 Paris France France

This paper deals with the vehicle routing problems for urban good distribution. The mix fleet size problem is a variant of the vehicle routing problem called Heterogeneous Fleet Vehicle Routing Problem (HFVRP). The objective is to design a set of routes in order to minimize the sum of the costs. The purpose of this study is to develop a tabu search (TS) heuristic to solve the HFVRP. The initial solution is obtained by a modified Clarke & Wright saving algorithm than treated by some fundamental and others new concepts of the TS algorithm. Our tabu search algorithm uses a new procedure called Fusion in parallel with the split procedure in order to explore new search spaces. In addition, a number of neighborhood structure are combined together in a process for intensifying the local search. Besides, the proposed algorithm is boosted with an adaptive memory algorithm, known as probabilistic diversification and intensification. On several benchmark instances, the TS produces high-quality solutions, including two new best solutions for small sized instances. The results obtained illustrate the effectiveness of the approach and its applicability to routing problems. © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Vehicle routing Benchmarking Fleet operations Learning algorithms Routing algorithms tabu search Vehicles Adaptive memory High quality solutions HVRP Last mile Local search Neighborhood structure tabu search algorithms Vehicle Routing Problems

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A tabu search Algorithm for Inter-terminal Container Transport

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IFAC-PapersOnLine 2016年第3期49卷 413-418页

作者： Hu, Qu Luan, Xiaojie Corman, Francesco Lodewijks, Gabriel Dept. of Maritime and Transport Technology Delft University of Technology Mekelweg 2 2628 CD Delft Netherlands

This paper discusses the container transport problem between terminals. The inter-terminal transport (ITT) becomes increasingly important with the expansion of port area and the intermodal transport. A major challenge to optimize the container transport is to find the adequate algorithm to handle the large-scale transport demand and planning horizon. A time-space graph is used to formulate the ITT in this paper, and then a tabu search algorithm is proposed. In order to test the algorithm, we apply it to a transport network with 18 terminals at the Maasvlakte in Port of Rotterdam. Different tabu search components are tested with different demand scenarios. A comparison of the results obtained by CPLEX and by the tabu search algorithm is also addressed. Through the comparison we can find that the algorithm can find good solution quickly, and performs well even for large scale transport demands where exact approaches are unable to find good solutions. © 2016

关键词： tabu search Containers Learning algorithms Vehicle routing inter terminal transport Intermodal transport Large scale transport Multi commodity flow Port of Rotterdam tabu search algorithms Transport networks Transport problems

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Energy optimisation of single train operation based on tabu search

Energy optimisation of single train operation based on tabu ...

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International Journal of Simulation and Process Modelling

作者： Cao, Fang Liu, Shuqi State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University China

Amid concerns about rising energy prices and environmental issues, the optimisation of automatic train operation (ATO) is significant for energy-efficient operation of trains. Different from the previous researches, this paper presents a more accurate model of the train energy consumption by considering the control strategy of ATO. It then proposes two modifications of tabu search (TS) algorithm, which are named as up-down modification (UDM) and left-right modification (LRM), to optimise train recommended speed curve based on the presented model. The simulation results based on the Beijing Subway illustrate that the proposed approaches can achieve a good performance on energy reduction. Sensitivities of the parameters are analysed to illustrate that the proposed approach is practical and meaningful. In addition, the computation time is within 2 s, which is short enough to be applied in the real-time control of trains. Copyright © 2016 Inderscience Enterprises Ltd.

关键词： Energy efficiency Energy utilization Real time control tabu search Control strategies Energy efficient operations Optimisations Recommended speed curve tabu search algorithms

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Analyzing foreign exchange rates by rough set theory and directed acyclic graph support vector machines

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EXPERT SYSTEMS WITH APPLICATIONS 2010年第8期37卷 5993-5998页

作者： Pai, Ping-Feng Chen, Shi-Yu Huang, Chao-Wei Chang, Ya-Hsin Natl Chi Nan Univ Dept Informat Management Puli 545 Nantou Taiwan Natl Chi Nan Univ Dept Int Business Studies Puli 545 Nantou Taiwan

Rough set theory (RST) and directed acyclic graph support vector machines (DAGSVM) are two emerging techniques in dealing with classification problems. The RST approach is able to select important features and generate rules from data. The SVM technique is powerful in solving classification problems with high generalization ability by applying the structure risk minimization principle. However, one particular model cannot capture all data patterns easily. This investigation presents a hybrid RST and DAGSVM model (RSTDAGSVM) to exploit the unique strengths of both RST and SVM in analyzing the movements of exchange rates. In the proposed hybrid model, the RST approach is used to extract the rules of exchange rate changes: and the DAGSVM technique is employed to deal with situations that cannot be included in the RST model. In addition, an immune algorithm and tabu search (1A/TS) method is applied to select parameters of SVM models. Experimental results reveal that the developed model achieves more accurate prediction results than either the RST model or the DAGSVM model on its own. Thus, the presented RSTDAGSVM model is a promising alternative for analyzing exchange rates. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Foreign exchange Rough set theory Directed acyclic graph support vector machines Immune algorithms tabu search algorithms

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Computation of the resonant frequency of electrically thin and thick rectangular microstrip antennas with the use of fuzzy inference systems

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INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING 2000年第2期10卷 108-119页

作者： Özer, S Güney, K Kaplan, A Erciyes Univ Intelligent Antenna Design Res Grp Dept Elect Engn Fac Engn TR-38039 Kayseri Turkey Erciyes Univ Intelligent Antenna Design Res Grp Sch Aviat TR-38039 Kayseri Turkey

A new method for calculating the resonant frequency of electrically thin and thick rectangular microstrip antennas, based on the fuzzy inference systems, is presented. The optimum design parameters of the fuzzy inference systems are determined by using the classical, modified, and improved tabu search algorithms. The calculated resonant frequency results are in very good agreement with the experimental results reported elsewhere. (C) 2000 John Wiley & Sons, Inc.

关键词： microstrip antenna resonant frequency fuzzy inference systems tabu search algorithms

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A new robust approach for a production scheduling and delivery routing problem

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IFAC-PapersOnLine 2016年第12期49卷 886-891页

作者： Cheref, Azeddine Artigues, Christian Billaut, Jean-Charles Université François-Rabelais Tours/CNRS 64 av. J. Portalis Tours37200 France CNRS LAAS Univ de Toulouse 7 avenue du colonel Roche ToulouseF-31400 France

In a supply chain, two essential problems are the production and the distribution. These two problems used to be solved separately, but it is well known that considering them jointly may lead to a global optimization of the supply chain performances. In this paper, we incorporate the delivery plan of a vehicle into a single machine scheduling problem, representing a single manufacturing facility. We consider the simplified case where there is only one vehicle available to serve the customers, with infinite capacity. However, we assume that the data are known with uncertainty. The objective is to find a schedule and a delivery plan so that a robustness criteria is minimized, under a scenario-based uncertainty modeling. In contrast with standard robust optimization approaches for scheduling, we do not propose a single complete solution to the problem that has to be feasible w.r.t. all scenarios and minimizes a worst-case criterion over the scenarios. Instead, we adopt the recoverable robustness framework that considers first-stage decisions and second-stage recovery options. We propose for the first-stage a set of solutions by using the concept of groups of permutable jobs. At second stage, a greedy and online recovery algorithm exploits the revealed information about the jobs available to be scheduled or to be delivered at decision time. We propose two tabu search algorithms, one based on the standard robust optimization scheme and one based on the new approach. We compare the two robust heuristics on a set of randomly generated problem instances. © 2016

关键词： Scheduling algorithms Global optimization Job shop scheduling Production control Scheduling Stages Supply chains tabu search Uncertainty analysis First stage decisions groups of permutable jobs Integrated production Manufacturing facility Robust optimization Single machine scheduling problems Supply chain performance tabu search algorithms

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Dynamic Pick-Up and Delivery Optimization With Multiple Dynamic Events in Real-World Environment

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IEEE ACCESS 2019年 7卷 146209-146220页

作者： Sun, Baofeng Yang, Yue Shi, Junyan Zheng, Lili Jilin Univ Coll Transportat Changchun 130025 Jilin Peoples R China

Real-time city distribution strategies are highly dependent on dynamic environments, requiring timely responses to real-time changes due to various dynamic events that take place in the distribution system. Considering the influence of four kinds of real-time information on vehicle routing and vehicle scheduling, including new requests arriving gradually, old requests being modified or canceled, traffic congestion and vehicle breakdowns, a dynamic vehicle routing model based on a dynamic pick-up and delivery problem considering multiple dynamic events in a real-world environment (DPDP-MDE) is established. A dynamic algorithm framework is designed to solve the problem, the tabu search (TS) algorithm and the adaptive large neighborhood search (ALNS) algorithm are adopted to improve the quality of the initial solution, and the dynamic insertion method is adopted to solve the synchronization problem of unfixed requests (that is, unaccepted customer requests and modified requests) and new requests. The experimental results show that the model and dynamic algorithm framework proposed in this paper can effectively solve the dynamic pick-up and delivery problem with time windows (DPDP-TW). At different scheduling time horizons T, the TS algorithm improves the initial solution by an average of 3.11% and the ALNS algorithm by an average of 9.98%. Under different degrees of urgency, compared to the ALNS algorithm, the quality of the solution produced by the TS algorithm is not high, but the computation time is very small and it is relatively stable. Under different request sizes, the TS algorithm can obtain optimization results in 60s under four request levels, which gives it a significant advantage over the ALNS algorithm.

关键词： Dynamic pick-up and delivery problem dynamic events dynamic algorithm framework constructive algorithm tabu search algorithms adaptive large neighborhood search algorithms

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An improved support vector model in car-rental revenue forecast

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JOURNAL OF STATISTICS & MANAGEMENT SYSTEMS 2007年第3期10卷 427-437页

作者： Hong, Wei-Chiang Lai, Young-Jou Pai, Ping-Feng Yang, Shun-Lin Oriental Inst Technol Dept Informat Management 58 Sec 2Si Chuan Rd Taipei 220 Taiwan Dept Ind & Mfg Syst Engn Manhattan KS 66502 USA Natl Chi Nan Univ Dept Informat Management Nantou 545 Taiwan Da Yeh Univ Dept Ind & Technol Management Changhua 51505 Taiwan

Monthly revenue per unit (RPU), measured by the total monthly revenue divided by the total monthly number of cars in the fleet, is one of the most popular profitability assessments in the car-rental industry. Because pricing decision is influenced by profit a lot, accurate forecast of RPU is thus useful for pricing in car-rental industry. Support vector regression (SVR) is an emerging forecast technique and successfully applied in many domains. The aim of this study is to investigate the feasibility of SVR in RPU forecast. Because SVR model contains three parameters influencing the forecasting accuracy, this work treats the forecasting error as an objective and employs tabu search (TS) algorithms to minimize the forecasting error. Actual RPU data are used to depict the forecasting performance of the improved SVR model. Two forecasting model, namely the general regression neural network (GRNN) model and the autoregressive integrated moving average (ARIMA) model, are used to forecast the same RPU data. Simulation results indicate that the improved SVR model is superior to the other models in terms of forecasting accuracy.

关键词： Forecast car-rental industry support vector regression tabu search algorithms general regression neural networks autoregressive integrated moving average

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