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Scheduling multiple agile earth observation satellites with an edge computing framework and a constructive heuristic algorithm

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JOURNAL OF SYSTEMS ARCHITECTURE 2019年 95卷 55-66页

作者： He, Yongming Chen, Yingwu Lu, Jimin Chen, Cheng Wu, Guohua Natl Univ Def Technol Coll Syst Engn Changsha 410073 Hunan Peoples R China Cent S Univ Sch Traff & Transportat Engn Changsha 410075 Hunan Peoples R China

The effective scheduling of multiple agile earth observation satellites plays a key role in improving the efficiency of the agile satellite observation system. Due to the complex constraints and large solution space (increases exponentially with the problem size), it has been a big challenge to effectively solve the multiple agile satellites scheduling problem. In this study, an edge computing framework is proposed in order to solve this problem in a flexible manner. In this framework, a central node and several edge nodes are included. The central node corresponds to the operation center of the satellite observation system while each edge node corresponds to an agile satellite. The central node filters tasks for edge nodes according to the time of scheduling period and visible time windows. Tasks in each edge node are scheduled according to the order of scheduling periods by a constructive heuristic algorithm based on the density of residual tasks (HADRT). The efficiency of this algorithm is proved. The time and space complexity are analyzed in detail. The proposed method is compared with other three advanced methods, and the experimental results show that HADRT could achieve higher task completion rate and reward rate than other algorithms with acceptable computing time.

关键词： Agile earth observation satellites scheduling Edge computing Optimization model constructive heuristic algorithm

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Transmission Expansion Planning Via a constructive heuristic algorithm in Restructured Electricity Industry

Transmission Expansion Planning Via a Constructive Heuristic...

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3rd International Conference on Electric Power and Energy Conversion Systems (EPECS)

作者： Khorasani, H. Pourakbari-Kasmaei, M. Romero, R. Univ Estadual Paulista Dept Elect & Comp Engn Ilha Solteira SP Brazil

ISBN: (纸本)9781479906871;9781479906888

The transmission expansion planning problem in modern power systems is a large-scale, mixed-integer, nonlinear and non-convex problem. this paper presents a new mathematical model and a constructive heuristic algorithm (CHA) for solving transmission expansion planning problem under new environment of electricity restructuring. CHA finds an acceptable solution in an iterative process, where in each step a circuit is chosen using a sensitivity index and added to the system. The proposed model consider multiple generation scenarios therefore the methodology finds high quality solution in which it allows the power system operate adequacy in an environment with multiple generators scenarios. Case studies and simulation results using test systems show possibility of using constructive heuristic algorithm in an open access system.

关键词： Transmission expansion planning constructive heuristic algorithm Open access Multiple generating scenarios hybrid model

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Demand planning of a nearly zero energy building in a PV/grid-connected system

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RENEWABLE ENERGY FOCUS 2023年 45卷 220-233页

作者： Fiorotti, Rodrigo Yahyaoui, Imene Rocha, Helder R. O. Honorato, Icaro Silva, Jair Tadeo, Fernando Fed Inst Espirito Santo Dept Electrotechnol Vitoria Brazil Univ Rey Juan Carlos I Madrid Appl Math Sci & Mat Engn & Elect Dept Madrid Spain Univ Fed Espirito Santo Elect Engn Dept Vitoria Brazil Univ Valladolid Dept Syst & Proc Engn Valladolid Spain

The energy consumption planning of smart homes connected to a grid with flexible power pricing, and complemented with a local PV installation, is studied. Advanced energy management is necessary to implement the Nearly Zero Energy Building (nZEB) concept in these smart homes. To do so, in the Energy Management System, it is essential to consider the flexibility provided by power pricing schemes, the distributed generation from renewable energies and the use of smart household appliances. This paper studies a novel formulation that depends on the comfort index required by the user, the PV power production, and the price variation of the grid energy. The study is performed on two levels: in the first, a metaheuristic multi-start, consisting of two steps, constructive heuristics and refinement heuristics (local search), is proposed to regulate the power demand of household appliances. The second level consists of determining the optimum PV installation that ensures the economic viability of the plant. The novelty of the paper is that the user defines a desired comfort level as input data, and the algorithm defines a demand plan that meets this comfort at the lowest possible cost. Six real case studies were carried out, considering the insertion of photovoltaic generation, to evaluate the performance of the proposed model from a technical and economic point of view. The results show that the proposed approach allows user requirements to be fulfilled and the energy production cost to be minimized. Without needing to reduce user comfort, the proposed demand planning algorithm can reduce the energy cost by 48.07 %. In this same scenario, combining the proposed method and the insertion of a photovoltaic system com-posed of 15 modules (Scenario 6), the total energy cost is reduced by 73.90 %.(c) 2023 Elsevier Ltd. All rights reserved.

关键词： Demand planning Photovoltaic power Comfort index Smart home Multi-start constructive heuristic algorithm

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Angular bisector insertion algorithm for solving small-scale symmetric and asymmetric traveling salesman problem

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JOURNAL OF COMBINATORIAL OPTIMIZATION 2022年第1期43卷 235-252页

作者： Lin, Jian Zeng, Xiangfei Liu, Jianxun Li, Keqin Hunan Univ Sci & Technol Key Lab Knowledge Proc & Networked Mfg Xiangtan 411201 Peoples R China SUNY Coll New Paltz Dept Comp Sci New York NY 12561 USA

Different algorithmic performances are required in different engineering fields for solving both the symmetric and asymmetric traveling salesman problem (STSP and ATSP), both of which are commonly referred to as TSP. In the background of small-scale TSP, according to the principle of the optimal Hamiltonian loop, this paper describes an angular bisector insertion algorithm (ABIA) that can solve TSP. The main processes of ABIA are as follows. First, the angular bisector of the point group is constructed. Second, the farthest vertex perpendicular to the angular bisector is identified as the search criterion. Finally, for both STSP and ATSP, initial loop formation rules and vertex insertion rules are constructed. Experiments were conducted for all STSP and ATSP instances with up to 100 points in the TSPLIB database. The performance of ABIA was compared with that of the 2-point farthest insertion algorithm, convex hull insertion algorithm, branch-and-bound algorithm, and a genetic algorithm. The experimental results show that, for small-scale TSP (up to 40 points), the runtime of ABIA is second only to the convex hull insertion algorithm, and the gap between ABIA and the optimal solution is second only to the exact algorithm. ABIA offers good overall performance in solving small-scale TSP.

关键词： Angle bisector insertion algorithm Asymmetric traveling salesman problem (ATSP) constructive heuristic algorithm Hamiltonian cycle Traveling salesman problem (TSP)

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Multi-strategy hybrid heuristic algorithm for single container weaklyheterogeneous loading problem

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COMPUTERS & INDUSTRIAL ENGINEERING 2022年 170卷

作者： Zhang, Dezhen Gu, Chenhao Fang, Hui Ji, Chengtao Zhang, Xiuguo Dalian Maritime Univ Coll Informat Sci & Technol Dalian Peoples R China Loughborough Univ Dept Comp Sci Loughborough LE11 3TU Leics England Xian Jiaotong Liverpool Univ Sch Adv Technol Dept Comp Suzhou Peoples R China

Three-dimensional single container weakly heterogeneous loading problem is one of the most classical taskswhich has various applications in manufacture and logistics industry. Solving this problem could improvetransportation efficiency to bring great benefit to shipping customers. During the last two decades, manyheuristic, meta-heuristic and hybrid algorithms have been proposed to maximize container volume utilizationto reduce the waste of container space significantly. Despite their success in many real-world applications, itis still a challenging task to recommend satisfactory loading levels within a limited time frame when clientsapproach for options of different combinations of shipping items. In this paper, we propose a novel multi-strategy hybrid heuristic algorithm to achieve timely planning for clients in a required short time *** specific, a probabilistic model is used to combine the strength of two optimization strategies, i.e. an antcolony method and a constructive greedy method, to speed up the optimization process and ensure betterconvergence. In addition, a tree pruning strategy is designed to further improve the efficiency of the hybridheuristic algorithm. Extensive experiments demonstrate the effectiveness of our method in terms of bothvolume utilization rate and algorithm processing speed compared to state-of-the-art methods. Based on thecomparison results by using BR dataset, we achieved averagely 94.31% volume utilization rate and 50.16 s processing speed, which is the best performance by considering both algorithm effectiveness and ***, our proposed method has been deployed in a real business case to provide plan solutions to individualcustomer shipping requests and achieved high customer satisfaction rate

关键词： 3D-CLP Weakly heterogeneous single container loading problem Ant colony algorithm constructive heuristic algorithm Multi-strategy optimization

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New construction heuristic algorithm for solving the vehicle routing problem with time windows

IET COLLABORATIVE INTELLIGENT MANUFACTURING

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IET COLLABORATIVE INTELLIGENT MANUFACTURING 2019年第3期1卷 90-96页

作者： Liu, Jun Feng, Shuo Niu, Qun Ji, Lijuan Lanzhou Univ Technol Sch Mech & Elect Engn Lanzhou Peoples R China

The vehicle routing problem with time windows (VRPTW) is the most important and widely studied combinational optimisation problem. However, most constructive heuristics create a new path when the customer violates the constraint and cannot insert into any existing path, causing the time window constraint to be tight and generating more paths. Aiming at the above problems, a new constructive heuristic algorithm is proposed. The algorithm firstly uses the convex hull of the customer location to determine the initial seed client and reduces the redundant path;meanwhile, the calculation method of the traditional optimal insertion position is improved, and the calculation efficiency is improved to some extent;in addition, for customers who cannot insert any feasible path, the exchange operator is introduced to give the current solution a disturbance instead of directly creating a new seed client and a new path to further reduce the redundant path. The experimental results show that the algorithm can effectively solve the close time window of VRPTW for evenly distributed customers, and even provide a strict time window for evenly distributed customers and a certain amount of hybrid geographic cluster customers.

关键词： search problems optimisation vehicle routing redundant path VRPTW evenly distributed customers strict time window hybrid geographic cluster customers construction heuristic algorithm vehicle routing problem constructive heuristics time window constraint constructive heuristic algorithm customer location initial seed client combinational optimisation problem

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High-performance hybrid genetic algorithm to solve transmission network expansion planning

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IET GENERATION TRANSMISSION & DISTRIBUTION 2017年第5期11卷 1111-1118页

作者： Gallego, Luis A. Garces, Lina P. Rahmani, Mohsen Romero, Ruben A. Univ Estadual Londrina Dept Elect Engn Londrina Brazil Univ Fed Goias Elect Mech & Comp Engn Sch Goiania Go Brazil Carnegie Mellon Univ Engn & Publ Policy Dept Pittsburgh PA 15213 USA Univ Estadual Paulista Dept Elect Engn Ilha Solteira Brazil

In this study, a high-performance hybrid genetic algorithm (HGA) is proposed to solve static and multistage transmission network expansion planning (TNEP) problem. The main features of the HGA are: (i) it avoids homogenised solutions by using a special genetic algorithm as the backbone of the procedure, (ii) uses a powerful path-relinking algorithm for the deep exploration of local solutions, (iii) employs an efficient constructive heuristic algorithm for finding high-quality initial solutions and for improving solution qualities and (iv) uses a fast relaxation strategy for solving the linear programming problems required for calculating the fitness functions. This procedure will result in an intelligent exploration of a large search space in less amount of time. The proposed methodology is tested with three electrical systems: South Brazilian 46-bus, Colombian 93-bus and the North-Northeast Brazilian 87-bus.

关键词： power transmission planning genetic algorithms linear programming high-performance hybrid genetic algorithm transmission network expansion planning static transmission network expansion planning problem multistage TNEP problem high-performance HGA path-relinking algorithm constructive heuristic algorithm fast relaxation strategy linear programming problem fitness function South Brazilian 46-bus electrical system Colombian 93-bus electrical system North-Northeast Brazilian 87-bus electrical system

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A constructive heuristic algorithm for Distribution System Planning

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IEEE TRANSACTIONS ON POWER SYSTEMS 2010年第3期25卷 1734-1742页

作者： Lavorato, Marina Rider, Marcos J. Garcia, Ariovaldo V. Romero, Ruben Univ Estadual Campinas Dept Elect Energy Syst Campinas SP Brazil UNESP Univ Estadual Paulista Dept Engn Eletr Fac Engn Ilha Solteira Ilha Solteira SP Brazil

A constructive heuristic algorithm (CHA) to solve distribution system planning (DSP) problem is presented. The DSP is a very complex mixed binary nonlinear programming problem. A CHA is aimed at obtaining an excellent quality solution for the DSP problem. However, a local improvement phase and a branching technique were implemented in the CHA to improve its solution. In each step of the CHA, a sensitivity index is used to add a circuit or a substation to the distribution system. This sensitivity index is obtained by solving the DSP problem considering the numbers of circuits and substations to be added as continuous variables (relaxed problem). The relaxed problem is a large and complex nonlinear programming and was solved through an efficient nonlinear optimization solver. Results of two tests systems and one real distribution system are presented in this paper in order to show the ability of the proposed algorithm.

关键词： AMPL constructive heuristic algorithm distribution system planning KNITRO mixed binary nonlinear programming power systems optimization

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Evaluation of the Performance of Space Reduction Technique Using AC and DC Models in Transmission Expansion Problems 13

Evaluation of the Performance of Space Reduction Technique U...

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13th International Conference on the European Energy Market (EEM)

作者： Gomes, Phillipe Vilaca Saraiva, Joao Tome Univ Porto Fac Engn Dept Engn Eletrotecn & Comp INESC TEC Rua Campo Alegre 823 P-4100 Oporto Portugal Univ Porto Fac Engn Dept Engn Eletrotecn & Comp FEUP DEEC Rua Campo Alegre 823 P-4100 Oporto Portugal

ISBN: (纸本)9781509012985

Transmission Expansion Planning (TEP) is an optimization problem that has a non-convex and combinatorial search space so that several solution algorithms may converge to local optima. Therefore, many works have been proposed to solve the TEP problem considering its relaxation or reducing its search space. In any case, relaxation and reduction approaches should not compromise the quality of the final solution. This paper aims at analyzing the performance of a search space technique using a constructive heuristic algorithm (CHA) admitting that the TEP problem is then solved using a Discreet Evolutionary Particle Swarm Optimization (DEPSO). On one hand the reduction quality is performed by analyzing whether the optimal expansion routes are included in the CHA constrained set and, on the other hand, the relaxation quality of the DC model is analyzed by checking if the optimal solution obtained with it violates any constraint using the AC model. The simulations were performed using three different test systems. The results suggest that the proposed CHA provides very good results in reducing the TEP search space and that the adoption of the DC model originates several violations if the full AC model is used to model the operation of the power system.

关键词： Multi-Year Transmission Expansion Planning constructive heuristic algorithm Discrete Evolutionary Particle Swarm Optimization

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Multi-step simultaneous changes constructive heuristic algorithm for Transmission Network Expansion Planning

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ELECTRIC POWER SYSTEMS RESEARCH 2009年第4期79卷 586-594页

作者： Bustamante-Cedeno, Enrique Arora, Sant Univ Minnesota Dept Mech Engn Ind & Syst Engn Div Minneapolis MN 55455 USA

In this paper, a constructive heuristic algorithm (CHA) is presented to solve the Transmission Network Expansion Planning Problem (TNEP), a complex non-convex Mixed Integer Non-Linear Programming (MINLP) problem with multiple local minima. In the proposed algorithm, the non-linearities are resolved through the following feature: when discrete decision variables are given, the model becomes linear in the continuous variables. A CHA is developed which improves the current solution by implementing multiple step simultaneous changes over a number of saturated transmission lines, in contrast to the approach traditionally followed. which implements one change at a time. Solutions to test problems are computed. (C) 2008 Elsevier B.V. All rights reserved.

关键词： Transmission Network Expansion Planning constructive heuristic algorithm Mixed Integer Non-Linear Programming Non-convex optimization Power deregulation

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