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GNN Representation Learning and Multi-Objective Variable Neighborhood Search Algorithm for Wind Farm Layout Optimization
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作者 Yingchao Li JianbinWang HaibinWang 《Energy Engineering》 EI 2024年第4期1049-1065,共17页
With the increasing demand for electrical services,wind farm layout optimization has been one of the biggest challenges that we have to deal with.Despite the promising performance of the heuristic algorithm on the rou... With the increasing demand for electrical services,wind farm layout optimization has been one of the biggest challenges that we have to deal with.Despite the promising performance of the heuristic algorithm on the route network design problem,the expressive capability and search performance of the algorithm on multi-objective problems remain unexplored.In this paper,the wind farm layout optimization problem is defined.Then,a multi-objective algorithm based on Graph Neural Network(GNN)and Variable Neighborhood Search(VNS)algorithm is proposed.GNN provides the basis representations for the following search algorithm so that the expressiveness and search accuracy of the algorithm can be improved.The multi-objective VNS algorithm is put forward by combining it with the multi-objective optimization algorithm to solve the problem with multiple objectives.The proposed algorithm is applied to the 18-node simulation example to evaluate the feasibility and practicality of the developed optimization strategy.The experiment on the simulation example shows that the proposed algorithm yields a reduction of 6.1% in Point of Common Coupling(PCC)over the current state-of-the-art algorithm,which means that the proposed algorithm designs a layout that improves the quality of the power supply by 6.1%at the same cost.The ablation experiments show that the proposed algorithm improves the power quality by more than 8.6% and 7.8% compared to both the original VNS algorithm and the multi-objective VNS algorithm. 展开更多
关键词 GNN representation learning variable neighborhood search multi-objective optimization wind farm layout point of common coupling
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Hybrid artificial bee colony algorithm with variable neighborhood search and memory mechanism 被引量:56
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作者 FAN Chengli FU Qiang +1 位作者 LONG Guangzheng XING Qinghua 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2018年第2期405-414,共10页
Artificial bee colony(ABC) is one of the most popular swarm intelligence optimization algorithms which have been widely used in numerical optimization and engineering applications. However, there are still deficiencie... Artificial bee colony(ABC) is one of the most popular swarm intelligence optimization algorithms which have been widely used in numerical optimization and engineering applications. However, there are still deficiencies in ABC regarding its local search ability and global search efficiency. Aiming at these deficiencies,an ABC variant named hybrid ABC(HABC) algorithm is proposed.Firstly, the variable neighborhood search factor is added to the solution search equation, which can enhance the local search ability and increase the population diversity. Secondly, inspired by the neuroscience investigation of real honeybees, the memory mechanism is put forward, which assumes the artificial bees can remember their past successful experiences and further guide the subsequent foraging behavior. The proposed memory mechanism is used to improve the global search efficiency. Finally, the results of comparison on a set of ten benchmark functions demonstrate the superiority of HABC. 展开更多
关键词 artificial bee colony(ABC) hybrid artificial bee colony(HABC) variable neighborhood search factor memory mechanism
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Particle Swarm Optimization Embedded in Variable Neighborhood Search for Task Scheduling in Cloud Computing 被引量:1
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作者 郭力争 王永皎 +2 位作者 赵曙光 沈士根 姜长元 《Journal of Donghua University(English Edition)》 EI CAS 2013年第2期145-152,共8页
In cloud computing system,it is a hot and hard issue to find the optimal task scheduling method that makes the processing cost and the running time minimum. In order to deal with the task assignment,a task interaction... In cloud computing system,it is a hot and hard issue to find the optimal task scheduling method that makes the processing cost and the running time minimum. In order to deal with the task assignment,a task interaction graph was used to analyze the task scheduling; a modeling for task assignment was formulated and a particle swarm optimization (PSO)algorithm embedded in the variable neighborhood search (VNS) to optimize the task scheduling was proposed. The experimental results show that the method is more effective than the PSO in processing cost,transferring cost, and running time. When the task is more complex,the effect is much better. So,the algorithm can resolve the task scheduling in cloud computing and it is feasible,valid,and efficient. 展开更多
关键词 cloud computing particle swarm optimization PSO) task scheduling variable neighborhood search VNS)
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Particle swarm optimization with variable neighborhood search for multiobjective flexible job shop scheduling problem 被引量:1
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作者 Song Huang Na Tian Zhicheng Ji 《International Journal of Modeling, Simulation, and Scientific Computing》 EI 2016年第3期199-215,共17页
The simulation on benchmarks is a very simple and efficient method to evaluate the performance of the algorithm for solving flexible job shop scheduling model.Due to the assignment and scheduling decisions,flexible jo... The simulation on benchmarks is a very simple and efficient method to evaluate the performance of the algorithm for solving flexible job shop scheduling model.Due to the assignment and scheduling decisions,flexible job shop scheduling problem(FJSP)becomes extremely hard to solve for production management.A discrete multi-objective particle swarm optimization(PSO)and simulated annealing(SA)algorithm with variable neighborhood search is developed for FJSP with three criteria:the makespan,the total workload and the critical machine workload.Firstly,a discrete PSO is designed and then SA algorithm performs variable neighborhood search integrating two neighborhoods on public critical block to enhance the search ability.Finally,the selection strategy of the personal-best individual and global-best individual from the external archive is developed in multi-objective optimization.Through the experimental simulation on matlab,the tests on Kacem instances,Brdata instances and BCdata instances show that the modified discrete multi-objective PSO algorithm is a promising and valid method for optimizing FJSP with three criteria. 展开更多
关键词 variable neighborhood search particle swarm optimization flexible job shop scheduling
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Unmanned Aerial Vehicle Inspection Routing and Scheduling for Engineering Management
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作者 Lu Zhen Zhiyuan Yang +2 位作者 Gilbert Laporte Wen Yi Tianyi Fan 《Engineering》 SCIE EI CAS CSCD 2024年第5期223-239,共17页
Technological advancements in unmanned aerial vehicles(UAVs)have revolutionized various industries,enabling the widespread adoption of UAV-based solutions.In engineering management,UAV-based inspection has emerged as ... Technological advancements in unmanned aerial vehicles(UAVs)have revolutionized various industries,enabling the widespread adoption of UAV-based solutions.In engineering management,UAV-based inspection has emerged as a highly efficient method for identifying hidden risks in high-risk construction environments,surpassing traditional inspection techniques.Building on this foundation,this paper delves into the optimization of UAV inspection routing and scheduling,addressing the complexity introduced by factors such as no-fly zones,monitoring-interval time windows,and multiple monitoring rounds.To tackle this challenging problem,we propose a mixed-integer linear programming(MILP)model that optimizes inspection task assignments,monitoring sequence schedules,and charging decisions.The comprehensive consideration of these factors differentiates our problem from conventional vehicle routing problem(VRP),leading to a mathematically intractable model for commercial solvers in the case of large-scale instances.To overcome this limitation,we design a tailored variable neighborhood search(VNS)metaheuristic,customizing the algorithm to efficiently solve our model.Extensive numerical experiments are conducted to validate the efficacy of our proposed algorithm,demonstrating its scalability for both large-scale and real-scale instances.Sensitivity experiments and a case study based on an actual engineering project are also conducted,providing valuable insights for engineering managers to enhance inspection work efficiency. 展开更多
关键词 Engineering management Unmanned aerial vehicle Inspection routing and scheduling OPTIMIZATION Mixed-integer linear programming model variable neighborhood search metaheuristic
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Effective Hybrid Teaching-learning-based Optimization Algorithm for Balancing Two-sided Assembly Lines with Multiple Constraints 被引量:8
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作者 TANG Qiuhua LI Zixiang +2 位作者 ZHANG Liping FLOUDAS C A CAO Xiaojun 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2015年第5期1067-1079,共13页
Due to the NP-hardness of the two-sided assembly line balancing (TALB) problem, multiple constraints existing in real applications are less studied, especially when one task is involved with several constraints. In ... Due to the NP-hardness of the two-sided assembly line balancing (TALB) problem, multiple constraints existing in real applications are less studied, especially when one task is involved with several constraints. In this paper, an effective hybrid algorithm is proposed to address the TALB problem with multiple constraints (TALB-MC). Considering the discrete attribute of TALB-MC and the continuous attribute of the standard teaching-learning-based optimization (TLBO) algorithm, the random-keys method is hired in task permutation representation, for the purpose of bridging the gap between them. Subsequently, a special mechanism for handling multiple constraints is developed. In the mechanism, the directions constraint of each task is ensured by the direction check and adjustment. The zoning constraints and the synchronism constraints are satisfied by teasing out the hidden correlations among constraints. The positional constraint is allowed to be violated to some extent in decoding and punished in cost fimction. Finally, with the TLBO seeking for the global optimum, the variable neighborhood search (VNS) is further hybridized to extend the local search space. The experimental results show that the proposed hybrid algorithm outperforms the late acceptance hill-climbing algorithm (LAHC) for TALB-MC in most cases, especially for large-size problems with multiple constraints, and demonstrates well balance between the exploration and the exploitation. This research proposes an effective and efficient algorithm for solving TALB-MC problem by hybridizing the TLBO and VNS. 展开更多
关键词 two-sided assembly line balancing teaching-learning-based optimization algorithm variable neighborhood search positional constraints zoning constraints synchronism constraints
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An improved artificial bee colony algorithm for steelmaking–refining–continuous casting scheduling problem 被引量:12
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作者 Kunkun Peng Quanke Pan Biao Zhang 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2018年第8期1727-1735,共9页
Steelmaking–refining–Continuous Casting(SCC) scheduling is a worldwide problem, which is NP-hard. Effective SCC scheduling algorithms can help to enhance productivity, and thus make significant monetary savings. Thi... Steelmaking–refining–Continuous Casting(SCC) scheduling is a worldwide problem, which is NP-hard. Effective SCC scheduling algorithms can help to enhance productivity, and thus make significant monetary savings. This paper develops an Improved Artificial Bee Colony(IABC) algorithm for the SCC scheduling. In the proposed IABC, charge permutation is employed to represent the solutions. In the population initialization, several solutions with certain quality are produced by a heuristic while others are generated randomly. Two variable neighborhood search neighborhood operators are devised to generate new high-quality solutions for the employed bee and onlooker bee phases, respectively. Meanwhile, in order to enhance the exploitation ability, a control parameter is introduced to conduct the search of onlooker bee phase. Moreover, to enhance the exploration ability,the new generated solutions are accepted with a control acceptance criterion. In the scout bee phase, the solution corresponding to a scout bee is updated by performing three swap operators and three insert operators with equal probability. Computational comparisons against several recent algorithms and a state-of-the-art SCC scheduling algorithm have demonstrated the strength and superiority of the IABC. 展开更多
关键词 Artificial bee colony Steelmaking–refining–continuous casting Hybrid flowshop scheduling variable neighborhood search
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Intervention decision-making in MAV/UAV cooperative engagement based on human factors engineering 被引量:10
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作者 ZHONG Yun YAO Peiyang +1 位作者 WAN Lujun YANG Juan 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2018年第3期530-538,共9页
Aiming at the intervention decision-making problem in manned/unmanned aerial vehicle(MAV/UAV) cooperative engagement, this paper carries out a research on allocation strategy of emergency discretion based on human f... Aiming at the intervention decision-making problem in manned/unmanned aerial vehicle(MAV/UAV) cooperative engagement, this paper carries out a research on allocation strategy of emergency discretion based on human factors engineering(HFE).Firstly, based on the brief review of research status of HFE, it gives structural description to emergency in the process of cooperative engagement and analyzes intervention of commanders. After that,constraint conditions of intervention decision-making of commanders based on HFE(IDMCBHFE) are given, and the mathematical model, which takes the overall efficiency value of handling emergencies as the objective function, is established. Then, through combining K-best and variable neighborhood search(VNS) algorithm, a K-best optimization variable neighborhood search mixed algorithm(KBOVNSMA) is designed to solve the model. Finally,through three groups of simulation experiments, effectiveness and superiority of the proposed algorithm are verified. 展开更多
关键词 manned/unmanned aerial vehicle(MAV/UAV) intervention decision-making human factors engineering structural description K-best algorithm variable neighborhood search algorithm
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A Hybrid Heuristic Algorithm for Solving COVID-19’s Social Distancing at Universities Campus
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作者 Hassan Al-Tarawneh Khalid Al-Kaabneh +2 位作者 Aysh Alhroob Hazem Migdady Issam Alhadid 《Computer Systems Science & Engineering》 SCIE EI 2022年第6期933-944,共12页
Social distancing during COVID-19 has become one of the most important measures in reducing the risks of the spread of the virus. Implementing thesemeasures at universities is crucial and directly related to the phys... Social distancing during COVID-19 has become one of the most important measures in reducing the risks of the spread of the virus. Implementing thesemeasures at universities is crucial and directly related to the physical attendance ofthe populations of students, professors, employees, and other members on campus. This research proposes an automated scheduling approach that can help universities and schools comply with the social distancing regulations by providingassistance in avoiding huge assemblages of people. Furthermore, this paper proposes a novel course timetable-scheduling scheme based on four main constraints.First, a distance of two meters must be maintained between each student inside theclassroom. Second, no classrooms should contain more than 20% of their regularcapacity. Third, there would be no back-to-back classes. Lastly, no lectures shouldbe held simultaneously in adjacent classrooms. The proposed approach wasimplemented using a variable neighborhood search (VNS) approach with an adaptive neighborhood structure (AD-NS) to resolve the problem of scheduling coursetimetables at Al-Ahlyyia Amman University. However, the experimental resultsshow that the proposed techniques outperformed the standard VNS tested on university course timetabling benchmark dataset ITC2007-Track3. Meanwhile, theapproach was tested using datasets collected from the faculty of information technology at Al-Ahlyyia Amman University (Jordan). Where the results showed that,the proposed technique could help educational institutes to resume their regularoperations while complying with the social distancing guidelines. 展开更多
关键词 COVID-19 social distance variable neighborhood search adaptive neighborhood structure university course timetable
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A Two-phase Solution Algorithm for the Inventory Routing Problem with Time Windows
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作者 Pantelis Z. Lappas Manolis N. Kritikos George D. Ioannou 《Journal of Mathematics and System Science》 2017年第9期237-247,共11页
The main objective of this paper is to propose a two-phase solution algorithm for solving the Inventory Routing Problem with Time Windows (IRPTW), which has not been excessively researched in the literature. The sol... The main objective of this paper is to propose a two-phase solution algorithm for solving the Inventory Routing Problem with Time Windows (IRPTW), which has not been excessively researched in the literature. The solution approach is based on (a) a simple simulation for the planning phase (Phase I) and (b) the Variable Neighborhood Search Algorithm (VNS) for the routing phase (Phase II). Testing instances are established to investigate algorithmic performance, and the computational results are then reported. The computational study underscores the importance of integrating the inventory and vehicle routing decisions. Graphical presentation formats are provided to convey meaningful insights into the problem. 展开更多
关键词 ROUTING Inventory Routing Problem with Time Windows Simple Simulation variable neighborhood search
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MIP Formulations and Metaheuristics for Multi-Item Capacitated Lot-Sizing Problem with Non-Customer Specific Production Time Windows and Setup Times
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作者 Ridha Erromdhani Abdelwaheb Rebai 《American Journal of Operations Research》 2017年第2期83-98,共16页
Our research focuses on the development of two cooperative approaches for resolution of the multi-item capacitated lot-sizing problems with time windows and setup times (MICLSP-TW-ST). In this paper we combine variabl... Our research focuses on the development of two cooperative approaches for resolution of the multi-item capacitated lot-sizing problems with time windows and setup times (MICLSP-TW-ST). In this paper we combine variable neighborhood search and accurate mixed integer programming (VNS-MIP) to solve MICLSP-TW-ST. It concerns so a particularly important and difficult problem in production planning. This problem is NP-hard in the strong sense. Moreover, it is very difficult to solve with an exact method;it is for that reason we have made use of the approximate methods. We improved the variable neighborhood search (VNS) algorithm, which is efficient for solving hard combinatorial optimization problems. This problem can be viewed as an optimization problem with mixed variables (binary variables and real variables). The new VNS algorithm was tested against 540 benchmark problems. The performance of most of our approaches was satisfactory and performed better than the algorithms already proposed in the literature. 展开更多
关键词 variable neighborhood Decomposition search Formatting Metaheuristics Production Planning Capacitated Lot Sizing Mixed Integer Programming Matheuristics Production Time Windows
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Optimization of fixed aviation support resource station configuration for aircraft carrier based on aircraft dispatch mission scheduling 被引量:5
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作者 Yujie LIU Wei HAN +1 位作者 Xichao SU Rongwei CUI 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2023年第2期127-138,共12页
Before the dispatch of the carrier-based aircraft,a series of pre-flight preparation operations need to be completed on the flight deck.Flight deck fixed aviation support resource station configuration has an importan... Before the dispatch of the carrier-based aircraft,a series of pre-flight preparation operations need to be completed on the flight deck.Flight deck fixed aviation support resource station configuration has an important impact on operation efficiency and sortie rate.However,the resource station configuration is determined during the aircraft carrier design phase and is rarely modified as required,which may not be suitable for some pre-flight preparation missions.In order to solve the above defects,the joint optimization of flight deck resource station configuration and aircraft carrier pre-flight preparation scheduling is studied in this paper,which is formulated as a two-tier optimization decision-making framework.An improved variable neighborhood search algorithm with four original neighborhood structures is presented.Dispatch mission experiment and algorithm performance comparison experiment are carried out in the computational experiment section.The correlation between the pre-flight preparation time(makespan)and flight deck cabin occupancy percentage is given,and advantages of the proposed algorithm in solving the mathematical model are verified. 展开更多
关键词 Carrier-based aircraft Multi-objective optimization Resource configuration SCHEDULING variable neighborhood search
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Vehicle flow formulation for two-echelon time-constrained vehicle routing problem 被引量:4
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作者 Hongqi Li Ming Bai +1 位作者 Yibin Zhao Changzhi Dai 《Journal of Management Science and Engineering》 2019年第2期75-90,共16页
Two-echelon routing problems,including variants such as the two-echelon vehicle routing problem(2E-VRP)and the two-echelon location routing problem(2E-LRP),involve assignment and location decisions.However,the two-ech... Two-echelon routing problems,including variants such as the two-echelon vehicle routing problem(2E-VRP)and the two-echelon location routing problem(2E-LRP),involve assignment and location decisions.However,the two-echelon time-constrained vehicle routing problem(2E-TVRP)that caters to from-linehaul-to-delivery practices does not involve assignment decisions.This routing problem variant for networks with two eche-lons has not yet attracted enough research interest.Localized or long-distance services suffer from the lack of the assignment decisions between satellites and customers.Therefore,the 2E-TVRP,rather than using assignment decisions,adopts time constraints to decide the routes on each of the two interacting echelons:large-capacity vehicles trans-port cargoes among satellites on the first echelon,and small-capacity vehicles deliver cargoes from satellites to customers on the second echelon.This study introduces a mixed integer linear programming model for the 2E-TVRP and proposes a heuristic algorithm that incorporates the savings algorithm followed by a variable neighborhood search phase.Illustrative examples are used to test the mathematical formulation and the heuristic and a case study is used to demonstrate that the heuristic can effectively solve realistic-size instances of the 2E-TVRP. 展开更多
关键词 Vehicle routing Two-echelon Time constraints Mixed integer linear programming variable neighborhood search
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