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第三十八届中国控制会议

作者： Feng Zou Debao Chen Yongqi Zhao School of Physics and Electronic Information HuaiBei Normal University

In this paper, a decomposition-based multi-objective backtracking search algorithm(DMOBSA) is proposed for personalized recommendation(PR) problems. In the proposed DMOBSA-PR, an effective individual representation is designed based on the characteristics of PR problems. Moreover, the new crossover and mutation operation in the framework of the BSA algorithm are introduced to update individuals. Furthermore, a decomposition-based multi-objective framework is utilized to balance accuracy and diversity metrics. Finally, the simulation results on Movielens 100 K dataset show that DMOBSA-PR is effective compared with other algorithms.

关键词： Personalized Recommendation Multi-objective optimization backtracking search algorithm Decomposition

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Echo State Network prediction based on backtracking search Optimization algorithm 3

Echo State Network prediction based on Backtracking Search O...

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IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)

作者： Wu, Shihong Wang, Zhigang Ling, Darong Army Logist Univ PLA Chongqing Peoples R China YGSoft Inc Zhuhai Peoples R China

ISBN: (纸本)9781538662434

Echo state network is one of the latest research results of artificial neural network, it's most notable feature is the simple network structure. Only the connection weight matrix of the reservoir (hidden layer) to the output layer needs to be calculated. In this paper, we aim to provide a kind of the echo state network prediction method based on adaptive backtracking search optimization. The adaptive back search algorithm is introduced into the echo state network to optimize the connection weights matrix of the echo state network reservoir and the output layer, then to improve the echo state network prediction accuracy.

关键词： echo state network backtracking search algorithm time series prediction

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Energy-efficient permutation flow shop scheduling problem using a hybrid multi-objective backtracking search algorithm

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JOURNAL OF CLEANER PRODUCTION 2017年 144卷 228-238页

作者： Lu, Chao Gao, Liang Li, Xinyu Pan, Quanke Wang, Qi Huazhong Univ Sci & Technol Sch Mech Sci & Engn State Key Lab Digital Mfg Equipment & Technol Wuhan Peoples R China

Permutation flow shop scheduling problems (PFSPs) have been extensively studied because of its broad industrial applications. However, setup and transportation time are usually ignored in most research, which causes a huge gap between the theoretical research and practical application. Meanwhile, energy saving has attracted growing attention due to the advent of sustainable manufacturing. Thus, we investigate an energy-efficient PFSP with sequence-dependent setup and controllable transportation time from a real-world manufacturing enterprise. First of all, a novel multi-objective mathematical model considering both makespan and energy consumption is formulated based on a comprehensive investigation. Then, a hybrid multi-objective backtracking search algorithm (HMOBSA) is proposed to solve this problem. Furthermore, a new energy saving scenario is developed to simultaneously ensure the service span of machines and energy saving. Finally, to evaluate the effectiveness of the proposed HMOBSA and energy saving scenario, we compare our proposal with other two famous multi-objective algorithms including NSGA-II and MOEA/D by conducting a real-world case study. The experimental results indicate that the proposed HMOBSA is superior to NSGA-II and MOEA/D for this case. Additionally, the proposed energy saving scenario also outperforms its competitors. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Energy efficiency Permutation flow shop scheduling Controllable transportation time backtracking search algorithm Multi-objective optimization

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An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system

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NEUROCOMPUTING 2017年 237卷 175-184页

作者： Islam, Naz Niamul Hannan, M. A. Shareef, Hussain Mohamed, Azah Univ Kebangsaan Malaysia Dept Elect Elect & Syst Engn Bangi 43600 Selangor Malaysia Univ Tenaga Nas Coll Engn Dept Elect Power Engn Kajang 43000 Selangor Malaysia United Arab Emirates Univ Dept Elect Engn F-1 BldgLevel 1 Coll EngnPOB 15551 Al Ain U Arab Emirates

This paper deals with the backtracking search algorithm (BSA) optimization technique to solve the design problems of multi-machine power system stabilizers (PSSs) in large power system. Power system stability problem is formulated by an optimization problem using the LTI state space model of the power system. To conduct a comprehensive analysis, two test systems (2-AREA and 5-AREA) are considered to explain the variation of design performance with increase in system size. Additionally, two metaheuristic algorithms, namely bacterial foraging optimization algorithm (BFOA) and particle swarm optimization (PSO) are accounted to evaluate the overall design assessment. The obtained results show that BSA is superior to find consistent solution than BFOA and PSO regardless of system size. The damping performance that achieved from both test systems are sufficient to achieve fast system stability. System stability in linearized model is ensured in terms of eigenvalue shifting towards stability regions. On the other hand, damping performance in the non-linear model is evaluated in terms of overshoot and setting times. The obtained damping in both test systems ate stable for BSA based design. However, BFOA and PSO based design perform worst in case of large power system. It is also found that the performance of BSA is not affected for large numbers of parameter optimization compared to PSO, and BFOA optimization techniques. This unique feature encourages recommending the developed backtracking search algorithm for PSS design of large multi-machine power system.

关键词： Power system stability Power system oscillations Power system damping Power system stabilizer backtracking search algorithm Multi-machine power system

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A tool for solving stochastic dynamic facility layout problems with stochastic demand using either a Genetic algorithm or modified backtracking search algorithm

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2017年 190卷 146-157页

作者： Vitayasak, Srisatja Pongcharoen, Pupong Hicks, Chris Naresuan Univ Fac Engn Dept Ind Engn CORIA Phitsanulok 65000 Thailand Newcastle Univ Newcastle Univ Business Sch 5 Barrack Rd Newcastle Upon Tyne NE1 7RU Tyne & Wear England

Facility layout problems (FLP) involve determining the optimal placement of machines within a fixed space. An effective layout minimises costs. The total material travel distance is a key indicator of the efficiency of internal logistics. Changes in demand and product mix may alter the material flow. The dynamic facilities layout problem (DFLP) takes into account changes in demand and allows for the periodic redesign of facilities. Facility redesign may reduce the material flow cost, but there is a trade-off between material flow improvements and reorganisation costs. There is a limited literature on the redesign of facilities with stochastic demand, heterogeneous-sized resources and rectilinear material flow. The backtracking search algorithm (BSA) has been used to successfully solve a range of engineering problems, but it has not previously been used to solve operations management problems or the FLP. This paper outlines novel modified backtracking search algorithms (mBSAs) that solved the stochastic DFLP with heterogeneous sized resources. The combination of material flow and redesign costs were minimised. Three mBSA were benchmarked against the classical BSA and a Genetic algorithm (GA) using 11 benchmark datasets obtained from the literature. The best mBSA generated better solutions than the GA for large-size problems. The total costs for the layouts generated by the best mBSA were significantly lower than for the conventional BSA. The modifications to the BSA increased the diversity of candidate solutions, which increased the amount of exploration. The computational time required by the three mBSAs was up to 70% less than the GA. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： backtracking search algorithm Genetic algorithm Dynamic facility layout problem Stochastic demand

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A compound structure of ELM based on feature selection and parameter optimization using hybrid backtracking search algorithm for wind speed forecasting

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ENERGY CONVERSION AND MANAGEMENT 2017年第Jul.期143卷 360-376页

作者： Zhang, Chu Zhou, Jianzhong Li, Chaoshun Fu, Wenlong Peng, Tian Huazhong Univ Sci & Technol Sch Hydropower & Informat Engn Wuhan 430074 Peoples R China Hubei Key Lab Digital Valley Sci & Technol Wuhan 430074 Peoples R China Three Gorges Univ Sch Hydraul & Environm Engn Yichang 443002 Peoples R China

Reliable wind speed forecasting is essential for wind power integration in wind power generation system. The purpose of paper is to develop a novel hybrid model for short-term wind speed forecasting and demonstrates its efficiency. In the proposed model, a compound structure of extreme learning machine (ELM) based on feature selection and parameter optimization using hybrid backtracking search algorithm (HBSA) is employed as the predictor. The real-valued BSA (RBSA) is exploited to search for the optimal combination of weights and bias of ELM while the binary-valued BSA (BBSA) is exploited as a feature selection method applying on the candidate inputs predefined by partial autocorrelation function (PACF) values to reconstruct the input-matrix. Due to the volatility and randomness of wind speed signal, an optimized variational mode decomposition (OVMD) is employed to eliminate the redundant noises. The parameters of the proposed OVMD are determined according to the center frequencies of the decomposed modes and the residual evaluation index (REI). The wind speed signal is decomposed into a few modes via OVMD. The aggregation of the forecasting results of these modes constructs the final forecasting result of the proposed model. The proposed hybrid model has been applied on the mean half-hour wind speed observation data from two wind farms in Inner Mongolia, China and 10-min wind speed data from the Sotavento Galicia wind farm are studied as an additional case. Parallel experiments have been designed to compare with the proposed model. Results obtained from this study indicate that the proposed hybrid model can provide an effective modeling approach to capture the nonlinear characteristics of wind speed signal and thus providing more satisfactory forecasting results. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Wind speed forecasting Extreme learning machine backtracking search algorithm Variational mode decomposition Feature selection Parameter optimization

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backtracking search algorithm for solving economic dispatch problems with valve-point effects and multiple fuel options

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ENERGY 2016年第Part1期116卷 637-649页

作者： Modiri-Delshad, Mostafa Kaboli, S. Hr Aghay Taslimi-Renani, Ehsan Abd Rahim, Nasrudin Wisma R&D Univ Malaya UM Power Energy Dedicated Adv Ctr UMPEDAC Level 4Jalan Pantai Baharu Kuala Lumpur 59990 Malaysia King Abdulaziz Univ Renewable Energy Res Grp Jeddah 21589 Saudi Arabia

This paper presents backtracking search algorithm (BSA) for solving economic dispatch (ED) problems with considering valve-point loading effects, prohibited operating zones, and multiple fuel options. The proposed method is an evolutionary technique of optimization with simple structure and single control parameter to solve numerical optimization problems. It is a powerful method for effectively exploring the search space of an optimization problem to find the optimal solution within a low computation time. Different test systems with up to 160 generating units have been used to show the performance of BSA to solve ED problems with high nonlinearities. The results are compared with several methods of optimization to verify the high performance of BSA for solving the ED problems. Statistical analysis of the results among 50 independent runs has been carried out to validate the BSA as a highly robust method. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Valve-point loading effects Multiple fuel option Economic dispatch Non-convex Transmission loss backtracking search algorithm

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A Hybrid backtracking search algorithm for Permutation Flow-Shop Scheduling Problem Minimizing Makespan and Energy Consumption

A Hybrid Backtracking Search Algorithm for Permutation Flow-...

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IEEE International Conference on Industrial Engineering and Engineering Management (IEEE IEEM)

作者： Chen, Peng Wen, Long Li, Ran Li, Xinyu Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Hubei Peoples R China Jianghan Univ Sch Int Educ Wuhan 430056 Hubei Peoples R China

ISBN: (纸本)9781538609484

With the advent of sustainable manufacturing, energy consumption becomes an essential consideration in the scheduling problem. However, traditional permutation flow-shop scheduling problem (PFSP) always only considers the production efficiency as its objective. In this paper, a hybrid backtracking search (HBSA) is proposed to minimize both the makespan and energy consumption for PFSP. In HBSA, the simulated annealing (SA) is hybrid with original backtracking search to update the population and then a local search algorithm is applied. Considering the effects of different operators on BSA, we analyze the effectiveness of initialization, crossover, and mutation and use the efficient strategy to improve its performance. Finally, the proposed HBSA is tested on the several benchmark problems to evaluate its performance, and the results are compared with genetic algorithm and branch and bound algorithm. The results validate its effective.

关键词： Permutation flow-shop Scheduling backtracking search algorithm Makespan Energy consumption

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Power System Stability Enhancement by Designing Optimal PSS Employing backtracking search algorithm 6

Power System Stability Enhancement by Designing Optimal PSS ...

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6th International Conference on Clean Electrical Power (ICCEP)

作者： Shafiullah, Md Rana, Md Juel Coelho, L. S. Abido, M. A. King Fahd Univ Petr & Minerals Dept Elect Engn Dhahran Saudi Arabia Pontificia Univ Catolica Parana Ind & Syst Engn Grad Program Curitiba Parana Brazil Fed Univ Parana Curitiba Elect Engn Grad Program Dept Elect Engn Curitiba Parana Brazil

ISBN: (纸本)9781509046829

Interconnected power systems are critically vulnerable to instability due to the disturbances in anyone portion of the system. Even low-frequency oscillations and small disturbances may lead to an outage of the system. Properly tuned Power System Stabilizer (PSS) is an effective tool for the suppression of these oscillations. This paper proposes a novel approach to tune proportional-integral (PI), proportional-integral-derivative (PID) and lead-lag PSS for a single machine infinite bus (SMIB) network by using backtracking search algorithm (BSA) to damp out low-frequency oscillation. The efficacy of BSA tuned PSS has been investigated by comparing the simulation results with fixed gain conventional PSS. In addition, the damping ratio and Eigenvalues of the same network have been compared with genetic algorithm (GA) based tuned PSS.

关键词： backtracking search algorithm Damping Ratio Eigenvalues Genetic algorithm Power System Stabilizer Single Machine Infinite Bus System

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Wind Thermal Economic Emission Dispatch Solution Using Multi-Objective backtracking search algorithm 5

Wind Thermal Economic Emission Dispatch Solution Using Multi...

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5th International Renewable and Sustainable Energy Conference (IRSEC)

作者： Daqaq, Fatima Ouassaid, Mohamed Ellaia, Rachid Mohammed V Univ Mohammadia Sch Engn Engn Smart & Sustainable Syst Res Ctr Rabat Morocco

ISBN: (纸本)9781538628478

This paper treats the problem of Economic Emission Dispatch considering the wind power. This model of Wind Thermal Economic Emission Dispatch "WTEED" takes into account both wind turbine and thermal generators. The aim of "WTEED" is minimizing the level of atmospheric pollution and fuel cost. To characterize the impact of wind power, a closed form is derived in terms of the Incomplete Gamma Function (IGF). To solve the problem and find the optimum fuel cost, optimum emission and best compromise solution, a new algorithm has been applied named Multi-Objectives backtracking search algorithm "MOBSA". The proposed approach has been examined for standard IEEE 30-Bus test system, comprising six conventional thermal generators and two wind generators. The results found approve the effectiveness and robustness of the proposed technique and it was compared with other algorithms as SPEA, MALO, and GAEPSO.

关键词： economic dispatch emission dispatch wind power backtracking search algorithm Multi-Objectives Optimization

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