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3rd International Conference on Advanced Engineering Materials and Architecture Science (ICAEMAS)

作者： Wang, Y. M. Zhang, Z. Zheng, J. B. Tong, L. L. Zhejiang Sci Tech Univ Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9783038352679

This paper proposed a chaotic genetic algorithm (CGA) to solve the mixed integer programming problem (MIPP). The basic idea of this algorithm is to overcome the deficiency of genetic algorithm (GA) by introducing chaotic disturbances into the genetic search process. Two typical MIPP problems are used to evaluate the performances of the proposed CGA. Experimental results show that performances of the algorithm have been improved by the chaotic disturbances, such as, search ability, precision, stability and convergence speed or calculation efficiency. The proposed CGA algorithm is suitable for solving complicated practical MIPP problem.

关键词： chaotic genetic algorithm mixed integer programming problem chaotic

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A graph reinforcement LearningPowered Online-Computational task offloading and latency minimization framework for wireless mobile edge computing networks

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COGNITIVE SYSTEMS RESEARCH 2025年 91卷

作者： Agrawal, Akshat Agrawal, Aayush Verma, Nilesh Kumar Gopi, Arepalli Peda Naik, K. Jairam NIT Raipur Dept Comp Sci & Engn Raipur 492010 India Vignans Nirula Inst Technol & Sci Women Guntur 522009 India

Data processing capability of lower power networks can be improved by Mobile Edge Computing (MEC) extending to the wireless sensor networks and IoT. Creating a replication of MEC network with an offloading policy where a choice is made in the Wireless devices (WDs) for each computation task is the focus of this study. Deciding whether the task execution proceeds locally in the same environment or can be handed over to a remote MEC server, an optimized algorithm is needed which adopts task offloading decisions and wireless resource allocation in real time. But adopting this is a challenging solution to the real time fast combinatorial optimization problems, and impossible with the available traditional approaches. As a solution, heuristic algorithms encompassing Deep reinforcement learning (DRL) are emerging;however, it doesn't make fair use of connection data like device-to-device interaction in MEC network. Moreover, heuristic algorithms rely on precise mathematical models for MEC systems which brought a new theory to the stage. This study revolves around this emerging technique relying on Graph neural networks (GNNs) learns from graph data while forwarding messages in the network. Utilizing GNN benefits, a Graph reinforcement learning-based online offloading framework (GROO) is proposed in this research, where the offloading policy is visualized as a graph state migration and MEC as an acyclic graph. The GROO achieves the lowest weighted task response latency (0.96 s) as compared to the existing DRL method (1.32 s) whereas on unseen circumstances and complex network topologies, GROO achieved lowest average latency up to 25 %.

关键词： Task offloading Graph reinforcement learning Wireless mobile-edge computing mixed integer programming problem Task response latency Energy consumption

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Safe cooperative control of CAVs at signal-free intersection under realistic scenarios

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SICE JOURNAL OF CONTROL MEASUREMENT AND SYSTEM INTEGRATION 2024年第1期17卷 106-121页

作者： Nakai, Yuta Namerikawa, Toru Keio Univ Dept Syst Design Engn Yokohama 2238522 Japan

This research deals with the cooperative control of CAVs (Connected and Automated Vehicles) at signal-free intersection. CAVs communicate with each other and adjust their speeds to safely pass through the intersection without having to stop. This is expected to improve intersection throughput and reduce fuel consumption. In order to execute cooperative control, a two-stage control structure is considered. In the first stage, the merging time, defined for each CAV as the time at which the CAV reaches the intersection, is obtained by solving mixed integer linear programming (MILP). In the second stage, each CAV solves an optimal control problem to determine the control input that allows it to reach the intersection at the merging time obtained in the first stage. In this research, a nonlinear model that considers air resistance, rolling resistance, and slope resistance is used to take into account the real environment. We propose a method using a control barrier function to guarantee the safety of CAVs even with nonlinear models , and an input correction method using a disturbance observer to suppress modelling errors caused by complex dynamics. We also propose a method that consists of establishing a speed regulation zone to avoid the possibility of passing through an intersection at an unsafe speed to improve throughput. Finally, a comparison with previous studies shows the superiority of the proposed method in reducing fuel consumption.

关键词： Control barrier function optimal control signal-free intersection mixed integer programming problem CAV

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A mixed-integer programming Approach to Group Control of Elevator Systems with Destination Hall Call Registration

A Mixed-integer Programming Approach to Group Control of Ele...

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

作者： Wu, Y. Tanaka, S. Kyoto Univ Dept Elect Engn Kyoto Japan Kyoto Univ Inst Liberal Arts & Sci Kyoto Japan

ISBN: (纸本)9781538672204

In this research, we focus on group control of an elevator system with destination hall call registration where passengers can directly register destination floors at every elevator lobby. To improve the elevator performance when transporting passengers, finding the optimal passenger-to-car assignment and car routing is considered as a good way. We formulate the problem of optimizing passenger-to-car assignment and car routing as a mixed-integer programming problem to minimize the average waiting time of all passengers waiting at elevator lobbies. Then, we perform computer simulation using a commercial integer programming solver and examine the effectiveness of the proposed optimization model. A conventional approach which is applied in most current elevator system is also compared with our approach.

关键词： Destination hall call registration passenger-to-car assignment car routing mixed integer programming problem average waiting time

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Formulation and algorithms for route planning problem of plug-in hybrid electric vehicles

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OPERATIONAL RESEARCH 2018年第2期18卷 497-519页

作者： Murakami, Keisuke Kansai Univ 3-3-35 Yamate Suita Osaka 5648680 Japan

Electric vehicles have recently received increasing attention because of their positive environmental and economic impacts;however, such vehicles are still not gaining widespread popularity for practical use given the inconvenience of limited battery capacity and long recharge times. To compensate for these drawbacks, plug-in hybrid electric vehicles (PHEVs) have been proposed, which can be recharged using standard household plug-in sockets unlike normal hybrid vehicles. Thus, PHEVs can run for long distances using widely available electrical power. Scheduling routes for the efficient use of electrical power is essential for PHEVs to succeed. Therefore, in this paper, we consider the PHEV routing and scheduling problem. We first formulate this problem as a mixed-integer programming (MIP) problem. Next, we propose three algorithms using a labeling method for large-scale problems;an exact algorithm and two heuristic algorithms. Our computational experiments show that the routes obtained using our algorithms are cost-efficient;further, our heuristic algorithms are much faster than the MIP formulation.

关键词： Plug-in hybrid electric vehicle Routing and scheduling problem mixed integer programming problem Labeling algorithm

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Finding the fuzzy solutions of a general fully fuzzy linear equation system

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2016年第2期30卷 921-933页

作者： Kocken, Hale Gonce Ahlatcioglu, Mehmet Albayrak, Inci Yildiz Tech Univ Dept Math Engn Istanbul Turkey Yildiz Tech Univ Dept Math Istanbul Turkey

In this paper, a new algorithm is proposed to find the solutions of a general (square or nonsquare) Fully Fuzzy Linear Equation System (FFLS) with arbitrary trapezoidal fuzzy numbers, i.e. there are no sign restrictions on the variables or the parameters of the system. We introduce the "feasible (strong) fuzzy solution" and "approximate fuzzy solution" concepts, then accordingly "no solution" case of a general FFLS is defined. And a model is proposed by means of a mixed integer programming modelling of "min" and "max" concepts in the multiplication of two arbitrary trapezoidal fuzzy numbers. With the logic of goal programming, the objective function of this model is constructed within the deviation variables. Based on the proposed model, also an algorithm is presented to determine the nature of solutions of a general FFLS. The method is illustrated with some numerical examples. Our numerical results for the examples from the literature are analyzed within some distance functions.

关键词： General fully fuzzy linear equation system trapezoidal fuzzy number fuzzy decision making mixed integer programming problem feasible and approximate fuzzy solution

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Reducing Multivalued Discrete Variables in Solving Separable Task Assignment problems

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Journal of the Operations Research Society of China 2016年第1期4卷 97-110页

作者： Ling Gai Qing-Wei Jin Yuan Tian Yao-Huei Huang Department of Management Science and Engineering Shanghai UniversityShanghai 200444China Department of Management Science and Engineering Zhejiang UniversityHangzhou 310058China Edward P.Fitts Department of Industrial and Systems Engineering North Carolina State UniversityRaleighNC 27695-7906USA Southwest Jiaotong University Chengdu 610031China

In this paper,we introduce the separable task assignment problem(STAP)in which n separable tasks are assigned to m agents subject to agents’capacity *** objective is to minimize the costs that occur during the manufacturing and the communication between agents.A task is separable if it can be divided into two pieces,and both of them can be assigned individually or together to any agents.A separable task is considered as being assigned if and only if its two pieces are both *** several discrete(ternary)variables may be involved in STAP modeling,computing the problem in a reasonable time period is not an easy *** replace the ternary variables by binary and continuous variables through extending the logarithmic method introduced by Li et al.(INFORMS J Comput 25(4):643–653,2012)and Vielma et al.(Oper Res 58(2):303–315,2010).Our numerical experiments demonstrate that the newly generated model performs well in solving difficult separable task-assignment problems for pretty large scale of instance sizes.

关键词： Task-assignment problem Ternary variables Binary variables mixed integer programming problem

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Control of virtual power plant in microgrids: a coordinated approach based on photovoltaic systems and controllable loads

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IET GENERATION TRANSMISSION & DISTRIBUTION 2015年第10期9卷 921-928页

作者： Liu, Yun Xin, Huanhai Wang, Zhen Gan, Deqiang Zhejiang Univ Dept Elect Engn Hangzhou 310027 Peoples R China

Renewable energy sources (RESs) such as solar energy are cost-effective to meet part of the energy needs. However, the inherent fluctuation and intermittence of RESs may deteriorate the stability and security of power grids. Energy storage systems can mitigate the problem, but they are very expensive. For this reason, a coordinated control method of virtual power plant (VPP), which includes photovoltaic systems (PVs) and controllable loads, is proposed in this study so that the aggregated power output of the VPP can be flexibly adjusted in a wide range. To achieve this, power output of the PVs and operational modes of controllable loads are coordinated by solving a mixed integer programming (MIP) problem. Meanwhile, with a quadratic interpolation based active power control strategy, each PV can operate in a power dispatch mode and simultaneously estimate its maximum available power, which is an input to the MIP problem. Externally, the VPP can quickly adjust the aggregated power and achieve functions important to power systems with high penetration of distributed energy resources, such as primary frequency regulation. Simulation results validate the effectiveness of VPP in providing frequency support to an island microgrid.

关键词： power generation control distributed power generation photovoltaic power systems power grids power system security power system stability power control integer programming interpolation power generation dispatch virtual power plant control photovoltaic systems controllable loads renewable energy sources RESs solar energy power grid stability power grid security energy storage systems VPP coordinated control method mixed integer programming problem MIP problem quadratic interpolation based active power control strategy power dispatch mode power systems distributed energy resources primary frequency regulation island microgrid

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Hybrid particle swarm optimization with chaotic search for solving integer and mixed integer programming problems

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Journal of Central South University 2014年第7期21卷 2731-2742页

作者：谭跃谭冠政邓曙光 School of Information Science and Engineering Central South University School of Communication and Electronic Engineering Hunan City University

A novel chaotic search method is proposed,and a hybrid algorithm combining particle swarm optimization(PSO) with this new method,called CLSPSO,is put forward to solve 14 integer and mixed integer programming *** performances of CLSPSO are compared with those of other five hybrid algorithms combining PSO with chaotic search *** results indicate that in terms of robustness and final convergence speed,CLSPSO is better than other five algorithms in solving many of these ***,CLSPSO exhibits good performance in solving two high-dimensional problems,and it finds better solutions than the known ones.A performance index(PI) is introduced to fairly compare the above six algorithms,and the obtained values of(PI) in three cases demonstrate that CLSPSO is superior to all the other five algorithms under the same conditions.

关键词： particle swarm optimization chaotic search integer programming problem mixed integer programming problem

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Robust n-k contingency constrained unit commitment with ancillary service demand response program

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IET GENERATION TRANSMISSION & DISTRIBUTION 2014年第12期8卷 1928-1936页

作者： Aghaei, Jamshid Alizadeh, Mohammad-Iman Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran

Today, many Independent System Operators (ISOs) establish programs to manipulate the reserve provided by Demand Response (DR) in ancillary service markets. In this study, Ancillary Service DR (ASDR) programs, recently introduced by Federal Energy Regulatory Commission, is integrated to an n-k Contingency Constrained Unit Commitment problem to investigate the capability of the DR Providers (DRPs), newly added ancillary market participants, in mitigating the impacts of simultaneous multiple contingencies in a power system. In the proposed model, an n-k security criterion by which power balance constraint is satisfied under any contingency state comprising simultaneous outages in generation units is investigated in the presence of the ASDR programs. Demand side reserve is supplied by DRPs, which have the responsibility of aggregating and managing customer responses to offer a bid-quantity to the ISO. The proposed formulation is a mixed integer programming problem based on primal-dual optimisation, reported recently in literature. In addition, a detailed discussion about versatile effects of ASDR programs on n-k security criterion is presented to demonstrate the applicability of the proposed model.

关键词： power generation dispatch power generation scheduling integer programming demand side management power markets robust n-k contingency constrained unit commitment problem ancillary service demand response program Independent System Operators ISOs ancillary service DR program ASDR DR providers DRPs ancillary market participants power system power balance constraint generation units demand side reserve bid-quantity mixed integer programming problem primal-dual optimisation n-k security criterion

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