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tabu search algorithm for the Railroad Blocking Problem

JOURNAL OF TRANSPORTATION ENGINEERING 2013年第2期139卷 216-222页

作者： Yaghini, Masoud Ahadi, Hamid Reza Barati, Elaheh Saghian, Zahra Iran Univ Sci & Technol Sch Railway Engn Dept Rail Transportat Engn Tehran Iran Sharif Univ Technol Tehran Iran Iran Univ Sci & Technol Tehran Iran

The railroad blocking problem (RBP) is an important decision for freight railroad companies. The objective of this problem is to minimize the costs of delivering all commodities by deciding which interyard blocks to build and specifying the assignment of commodities to these blocks. In this paper, a mathematical model is presented for the RBP on Iran Railways. Its decision variables identify blocking scheme and demand assignment to these blocks. The RBP in medium and large sizes is not solvable with any commercial software available in the market. Therefore, a solution method based on tabu search algorithm is proposed for the suggested model. For evaluating the proposed algorithm, several simulated test problems are randomly generated and solved. The obtained results on the test problems are compared with those of solutions generated by CPLEX software. The comparison shows high efficiency and effectiveness of the proposed algorithm. The proposed model and solution method are applied to build a blocking plan for the Iranian railway. DOI:10.1061/(ASCE)TE.1943-5436.0000447. (C) 2013 American Society of Civil Engineers.

关键词： Rail transportation planning Railroad blocking problem Optimization tabu search algorithm Iran Railways Rail transportation Blocks Railroad stations Optimization models algorithms Iran

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tabu search algorithm for routing, modulation and spectrum allocation in elastic optical network with anycast and unicast traffic

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COMPUTER NETWORKS 2015年第Mar.14期79卷 148-165页

作者： Goscien, Roza Walkowiak, Krzysztof Klinkowski, Miroslaw Wroclaw Univ Technol European Res Ctr Network IntelliGence INnovat Enh Dept Syst & Comp Networks & ENGINE PL-50370 Wroclaw Poland Natl Inst Telecommun PL-04894 Warsaw Poland

The paper presents a novel method based on the standard tabu search (TS) approach, dedicated to solve the routing, modulation and spectrum allocation (RMSA) problem in elastic optical networks (EONs). The considered formulation of the RMSA problem covers simultaneously unicast (one-to-one) and anycast (one-to-one-of-many) traffic demands. This is a very important issue taking into account the fact that anycasting gains more and more importance in contemporary Internet due the growing popularity of services like cloud computing, content delivery networks, and video streaming. In this paper, we formulate RMSA as an integer linear programming (ILP) problem and we study four different objective functions, which are related to, respectively, cost, power consumption, maximum and average spectrum usage. We evaluate the performance of our TS method based on the comparison with both optimal results yielded by the CPLEX solver and the results obtained by reference heuristic algorithms proposed in the literature. Moreover, we evaluate benefits of the use of anycasting in EONs. The performed simulation experiments demonstrate that the proposed algorithm outperforms other reference methods. What is more, we show that the anycast transmission can provide significant savings compared to the typical unicast transmission. (C) 2015 Elsevier B.V. All rights reserved.

关键词： tabu search algorithm Routing Modulation and spectrum allocation Anycast traffic Elastic optical networks

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tabu search algorithm based general regression neural network for long term wind speed predictions

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AUTOMATIKA 2020年第4期61卷 657-669页

作者： Vidya, S. Janani, E. Srie Vidhya Kalasalingam Inst Technol Dept Comp Sci & Engn Virudunagar 626126 Tamil Nadu India Anna Univ Dept Comp Sci & Engn Madurai Tamil Nadu India

Accurate prediction of wind speed is needed as the wind power directly depends upon the wind speed. Because of the complex non-stationary and nonlinear characteristics of wind speed, it is difficult to achieve good prediction accuracy. Compared to the prediction models that use single algorithms, hybrid models always have higher accuracy. The decomposition algorithm called Empirical Mode Decomposition (EMD) is combined with the optimization algorithm named tabu search (TS) and General Regression Neural Network (GRNN) to achieve high precision and is proposed in this study. The performance of the proposed approach is evaluated using wind speed datasets of different cities in India. The detail of the proposed model is given as follows: EMD (Empirical Mode Decomposition) decomposes the original datasets of wind speed into intrinsic mode functions (IMFs). A partial autocorrelation function determines the number of neurons in the input layer of GRNN. An intelligent algorithm namely tabu search is used to optimize the neural networks globally. The proposed model has better prediction accuracy in long term wind speed forecasting.

关键词： Wind speed forecasting general regression neural network tabu search algorithm empirical mode decomposition partial auto-correlation function intrinsic mode functions

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tabu search algorithm for for Capacitated Vehicle Routing Problem

Tabu Search Algorithm for for Capacitated Vehicle Routing Pr...

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3rd International Conference on Advanced Engineering Materials and Technology (AEMT 2013)

作者： Ren, Chunyu Heilongjiang Univ Sch Informat Sci & Technol Harbin Peoples R China

ISBN: (纸本)9783037857649

The paper is focused on the capacitated vehicle routing problem. tabu search algorithm is an algorithm based on neighborhood search. According to the features of the problem, the essay centered the construct initial solution to build neighborhood structure. For the operation, 1-move and 2-opt were applied, it can also fasten the speed of convergence, and boost the search efficiency. Finally, the good performance of this algorithm can be proved by experiment calculation and concrete examples.

关键词： capacitated vehicle routing problem 1-move 2-opt tabu search algorithm

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tabu search algorithm Optimized ANN Model for Wind Power Prediction with NWP

Tabu Search Algorithm Optimized ANN Model for Wind Power Pre...

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1st International Conference on Smart Grid and Clean Energy Technologies (ICSGCE)

作者： Han, Shuang Li, Jinshan Liu, Yongqian North China Elect Power Univ Renewable Energy Sch Beijing 102206 Peoples R China State Grid Xin Yuan Construct Co Ltd Beijing 100053 Peoples R China

Wind power prediction is of great importance for the safety and stabilization of grids. The most important and difficult problem now is to enhance the prediction precision. BP (Backward Propagation) neural network has been used extensively in wind power prediction. But BP network is apt to getting into local minima and its convergence rate is slow. tabu search is a kind of intelligent algorithm, which can achieve the global optimizations. This paper put forward a wind power prediction model of BP neural network optimized by tabu search algorithm with memory function. The result shows that with appropriate input parameters, the wind power prediction model of neural network based on tabu search algorithm can improve the prediction precision as well as the convergence rate. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of University of Electronic Science and Technology of China (UESTC).

关键词： Wind power prediction ANN tabu search algorithm

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tabu search algorithm for Optimal Electric Water Heating Energy Management 12

Tabu Search Algorithm for Optimal Electric Water Heating Ene...

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12th IFAC Symposium on Control of Power and Energy Systems (CPES)

作者： El Bakali, Saida Ouadi, Hamid Fouad, Giri Gheouany, Saad Nada, Mounir Ismael, Jrhilifa Mohammed V Univ Rabat ERERA ENSAM Rabat Rabat Morocco UNICAEN Normandie Univ ENSICAEN LAC F-14000 Caen France

The aim of this paper is to develop an optimal energy management strategy for electric water heaters (EWHs), based on operational data such as photovoltaic (PV) production, ambient temperature (AT), water demand (WD), and fixed appliance consumption (FAC), electricity tariffs and user preferences. The proposed strategy uses a multi-objective tabu search (TS) algorithm to determine the optimal domestic hot water output over the next 24 hours based on this prior data. The aim is to minimize the electricity bill while maintaining a desired level of comfort, by keeping the water temperature within a range compatible with the user's thermal comfort. In addition, the temperature setpoint was varied according to operating conditions. A comparison with particle swarm optimization (PSO)-based management, which uses a similar strategy but employs the PSO algorithm for optimization, reveals that the proposed strategy achieves a significant 33.2% reduction in electricity costs and a 3.8% reduction in carbon emissions. Copyright (c) 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)

关键词： EWH energy management tabu search algorithm Multi-objective optimization

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A tabu search algorithm for distribution network optimization with discrete split deliveries and soft time windows

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2019年第6-Sup期22卷 15447-15457页

作者： Xia, Yangkun Fu, Zhuo Cent S Univ Sch Traff & Transportat Engn Changsha 410075 Hunan Peoples R China

To save the distribution network costs, the vehicle routing problem with split deliveries by order and soft time windows is studied. In this paper, the flexibility of the distribution system is enhanced via soft time windows, the requirement for non-split deliveries is loosened, and a new form of discrete split deliveries is defined. The new form of split deliveries by order is agreed for splitting. Giving considerations to split deliveries by order, soft time windows and working time constraints, a corresponding multi-objective mathematical model is constructed, and an adaptive tabu search algorithm with dynamic tabu list and multi-neighborhood structure is designed to solve the problem. The effectiveness of the new algorithm is verified by the example testing and comparison.

关键词： Vehicle routing problem Split deliveries by order Split deliveries tabu search algorithm Soft time windows Distribution

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Optimal power flow using tabu search algorithm

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2002年第5期30卷 469-483页

作者： Abido, MA King Fahd Univ Petr & Minerals Dept Elect Engn Dhahran 31261 Saudi Arabia

This paper presents an efficient and reliable tabu search (TS)-based approach to solve the optimal power flow (OPF) problem. The proposed approach employs TS algorithm for optimal settings of the control variables of the OPF problem. Incorporation of TS as a derivative-free optimization technique in solving OPF problem significantly reduces the computational burden. One of lite main advantages of TS algorithm is its robustness to its own parameter settings as well as the initial solution. In, addition, TS is characterized by its ability to avoid entrapment in local optimal solution and prevent cycling by using flexible memory of search history. The proposed approach has been examined on the standard IEEE 30-bus test system with different objectives and generator cost curves, The results are promising and show the effectiveness and robustness of lite proposed approach.

关键词： optimal power flow tabu search algorithm combinatorial optimization

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Application of multiple tabu search algorithm to solve dynamic economic dispatch considering generator constraints

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ENERGY CONVERSION AND MANAGEMENT 2008年第4期49卷 506-516页

作者： Pothiya, Saravuth Ngamroo, Issarachai Kongprawechnon, Waree Thammasat Univ Sch Commun Instrumentat & Control Sirindhorn Int Inst Technol Pathum Thani Thailand King Mongkuts Inst Technol Ladkrabang Fac Engn Dept Elect Engn Bangkok Thailand

This paper presents a new optimization technique based on a multiple tabu search algorithm (NITS) to solve the dynamic economic dispatch (ED) problem with generator constraints. In the constrained dynamic ED problem, the load demand and spinning reserve capacity as well as some practical operation constraints of generators, such as ramp rate limits and prohibited operating zone are taken into consideration. The NITS algorithm introduces additional mechanisms such as initialization, adaptive searches, multiple searches, crossover and restarting process. To show its efficiency, the NITS algorithm is applied to solve constrained dynamic ED problems of power systems with 6 and 15 units. The results obtained from the NITS algorithm are compared to those achieved from the conventional approaches, such as simulated annealing (SA), genetic algorithm (GA), tabu search (TS) algorithm and particle swarm optimization (PSO). The experimental results show that the proposed NITS algorithm approaches is able to obtain higher quality solutions efficiently and with less computational time than the conventional approaches. (c) 2007 Elsevier Ltd. All rights reserved.

关键词： dynamic economic dispatch genetic algorithm particle swarm optimization power system operation tabu search algorithm

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An improved tabu search algorithm for the fixed-spectrum frequency-assignment problem

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2003年第4期52卷 891-901页

作者： Montemanni, R Moon, JNJ Smith, DH Univ Glamorgan Sch Comp Pontypridd CF37 1DL M Glam Wales Univ Glamorgan Div Math Pontypridd CF37 1DL M Glam Wales

A tabu search algorithm with a dynamic tabu list for the fixed-spectrum frequency-assignment problem is presented. For cellular problems, the algorithm can be combined with an efficient cell reoptimization step. The algorithm is tested on several sets of test problems and compared with existing algorithms of established performance. In particular, it is used to improve some of the best existing assignments for COST 259 benchmarks. These results add support to the claim that the algorithm is the most effective available, at least when solution quality is a more important criterion than solution speed. The algorithm is robust and easy to tune.

关键词： fixed-spectrum problems radio-frequency assignment tabu search algorithm

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