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检索条件"任意字段=13th International Conference on Integer Programming and Combinatorial Optimization"

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An MILP Model for Distributed Energy System optimization

An MILP Model for Distributed Energy System Optimization

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16th international conference on Process Integration, Modelling and Optimisation for Energy Saving and Pollution Reduction (PRES)

作者： Haikarainen, Carl Pettersson, Frank Saxen, Henrik Abo Akad Univ Lab Heat & Flow Engn FI-20500 Turku Finland

ISBN: (纸本)9788895608266

Investigations regarding means to achieve savings in primary energy use and to decrease anthropogenic CO2 emissions have shown that improved energy efficiency has potential to offer a significant contribution to this cause. Considering energy networks and systems, improvements can be achieved by optimizing the structure of the energy chains and distribution networks. For instance, in the case of district heating, it is possible to find an optimal choice of energy supply and design of piping networks to provide the energy required by the customers. Additionally, heat storages and local small-scale energy contributions from e. g. heat pumps could provide benefits and should be taken into consideration. the complexity of the optimization problem increases when the choices of technologies and capacities as well as the network topologies need to be considered. Furthermore, a level of intricacy is added by the large differences in energy demand and temperature conditions between day and night and different seasons. A mixed-integer linear programming model for optimizing distributed energy systems, which takes into account the above mentioned aspects, is being developed and is presented herein. the model is tested with a case study concerning district heating in a locality in southern Finland.

关键词： District heating

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Exploiting the power of MIP solvers in MAXSAT

Exploiting the power of MIP solvers in MAXSAT

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16th international conference on theory and Applications of Satisfiability Testing, SAT 2013

作者： Davies, Jessica Bacchus, Fahiem Department of Computer Science University of Toronto Toronto ON M5S 3H5 Canada

ISBN: (纸本)9783642390708

maxsat is an optimization version of satisfiability. Since many practical problems involve optimization, there are a wide range of potential applications for effective maxsat solvers. In this paper we present an extensive empirical evaluation of a number of maxsat solvers. In addition to traditional maxsat solvers, we also evaluate the use of a state-of-the-art Mixed integer Program (mip) solver, cplex, for solving maxsat. mip solvers are the most popular technology for solving optimization problems and are also theoretically more powerful than sat solvers. In fact, we show that cplex is quite effective on a range of maxsat instances. Based on these observations we extend a previously developed hybrid approach for solving maxsat, that utilizes both a sat solver and a mip solver. Our extensions aim to take better advantage of the power of the mip solver. the resulting improved hybrid solver is shown to be quite effective. © 2013 Springer-Verlag.

关键词： integer programming

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A decentralized control strategy for energy retrofit planning of large-scale street lighting systems using dynamic programming

A decentralized control strategy for energy retrofit plannin...

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IEEE international conference on Automation Science and Engineering (CASE)

作者： Raffaele Carli Mariagrazia Dotoli Department of Electrical and Information Engineering of the Polytechnic of Bari Bari Italy

this paper addresses the energy management of large-scale urban street lighting systems. We propose a multi-stage decision-making procedure that supports the energy manager in determining the optimal energy retrofit plan of an existing public street lighting system. the problem statement is based on a quadratic integer programming formulation and aims at simultaneously reducing the energy consumption, ensuring an optimal allocation of the retrofit actions, and efficiently using the available budget. the proposed solution relies on a decentralized optimization algorithm that is based on discrete dynamic programming. the methodology is applied to a real street lighting system in the city of Bari, Italy.

关键词： Lighting Linear programming Dynamic programming optimization Energy management Decision making Urban areas

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On preemptive resource constrained scheduling: Polynomial-time approximation schemes

On preemptive resource constrained scheduling: Polynomial-ti...

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9th international integer programming and combinatorial optimization conference, IPCO 2002

作者： Jansen, Klaus Porkolab, Lorant Institut für Informatik und praktische Mathematik Christian-Albrechts-Universität zu Kiel Kiel24 098 Germany PricewaterhouseCoopers London United Kingdom

ISBN: (纸本)9783540478676

We study resource constrained scheduling problems where the objective is to compute feasible preemptive schedules minimizing the makespan and using no more resources than what are available. We present approximation schemes along with some inapproximibility results showing how the approximability of the problem changes in terms of the number of resources. the results are based on linear programming formulations (though with exponentially many variables) and some interesting connections between resource constrained scheduling and (multidimensional, multiple-choice, and cardinality constrained) variants of the classical knapsack problem. In order to prove the results we generalize a method by Grigoriadis et al. for the max-min resource sharing problem to the case with weak approximate block solvers (i.e. with only constant, logarithmic, or even worse approximation ratios). Finally we present applications of the above results in fractional graph coloring and multiprocessor task scheduling. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Linear programming

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A multi-stage renewal planning of an energy supply system for a hospital based on the mathematical optimization method 28

A multi-stage renewal planning of an energy supply system fo...

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28th international conference on Efficiency, Cost, optimization, Simulation and Environmental Impact of Energy Systems, ECOS 2015

作者： Yoshida, Shu Ito, Koich Yoshida, Akira Amano, Yoshiharu Research and Development Center Kansai Electric Power Co. Inc. Hyogo Japan Graduate School of Fundamental Science and Engineering Waseda University Tokyo Japan Research Institute for Science and Engineering Waseda University Tokyo Japan

ISBN: (纸本)9782955553909

the multi-stage renewal planning problem is studied here for an energy supply system installed into a hospital from the long- Term economic viewpoint by applying the mathematical optimization method. this problem is mathematically formulated as a large-scale mixed-integer linear programming one, and the average annual total cost during the evaluation period is set as the objective function to be minimized. In this problem, by taking the deterioration of performance efficiency of the existing pieces of equipment, the renewal system is assumed to be composed by installing new pieces of equipment with improved efficiency by reflecting technical progress. By optimizing the system's operational policy for hourly and seasonally changing energy demands through years of the evaluation period, the renewal years and the system's configurations at each multi-stages are determined optimally. A numerical study is carried out for a really existing hospital with total floor area of 25000m2, and many comprehensive and useful results are obtained by comparing 13 alternative renewal plans by using the CPLEX solver.

关键词： Hospitals

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Discrete optimization models for solving complex products design problems 9th

Discrete optimization models for solving complex products de...

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9th international conference on Discrete optimization and Operations Research, DOOR 2016

作者： Kolokolov, Alexander Artemova, Alexandra Adelshin, Alexander Kan, Irina Sobolev Institute of Mathematics Omsk Branch Pevtsova str. 13 Omsk644043 Russia Omsk State Technical University Pr. Mira 11 Omsk644050 Russia Omsk State Institute of Service Pevtsova str. 13 Omsk644043 Russia

the development and research of discrete optimization models with logical, resource and other constraints to solve complex products design problems are continued in the article. these models are based on the SAT problem and its generalizations. Particular attention is paid to the questions of design of series of products using special sets of components ("kernels") that have been suggested by the authors and allow to expand the variety of output products in various production branches. the results of computational experiments that reflect the prospects of the approach are presented. Copyright © by the paper's authors.

关键词： integer programming

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Parcel Sorting optimization in Double-Layer Automatic Sorting System 2nd

Parcel Sorting Optimization in Double-Layer Automatic Sortin...

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6th KES Annual international conference on Smart Education and e-Learning (KES SEEL) / 2nd KES international Symposium on Smart Transportation Systems (KES-STS)

作者： Tan, Zheyi Zhen, Lu Xiao, Liyang Sun, Qian Shanghai Univ Sch Management Shanghai Peoples R China

ISBN: (纸本)9789811386831;9789811386824

Fully automated sorting equipment plays a crucial role in modern distribution networks of the parcel service industry, and the efficiency of the sorting scheme is crucial for the sorting equipment. this study optimizes the sorting scheme for a type of double-layer sorting equipment, which adapts "component-sorting" strategy. "Component-sorting" refers to the method of sorting multiple parcels sent to the same destination by the same tray. the problem is formulated as an integer programming model. then, we propose an efficient variable neighbor taboo search to solve the problem within a short time. the experimental results show that the proposed solution method is suitable for solving the problem of interest.

关键词： Component-sorting Destination assignment problem Double variable neighbor taboo search Double-layer sorting equipment

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Two-Machine Flow Shop Scheduling Problem Under Linear Constraints 13th

Two-Machine Flow Shop Scheduling Problem Under Linear Constr...

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13th Annual international conference on combinatorial optimization and Applications, COCOA 2019

作者： Nip, Kameng Wang, Zhenbo Sun Yat-sen University Zhuhai China Department of Mathematical Sciences Tsinghua University Beijing China

ISBN: (纸本)9783030364113

We introduce a two-machine flow shop scheduling problem under linear constraints (2-FLC problem in short), in which the processing times of two stages of jobs are also decision variables and satisfy a system of linear constraints. the goal is to determine the processing times of each job, and to schedule the jobs to the two-machine flow shop such that the makespan, i.e., the completion time of all the jobs is minimized. this problem can find applications in various areas, such as industrial production and advertising planning. We study the computational complexity and algorithms for the 2-FLC problem. Particularly, we show that although the two-machine flow shop scheduling problem can be solved in polynomial time, the 2-FLC problem is generally NP-hard in the strong sense. then we consider the design and analysis of algorithms on various settings of the 2-FLC problem. In particular, we propose a polynomial time algorithm for the 2-FLC problem when there is a fixed number of constraints. For the general case, we first propose a simple 2-approximation algorithm, and then design a polynomial time approximation scheme (PTAS). © 2019, Springer Nature Switzerland AG.

关键词： Linear programming

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Approximation Algorithms for Maximum Coverage with Group Budget Constraints 11th

Approximation Algorithms for Maximum Coverage with Group Bud...

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11th Annual international conference on combinatorial optimization and Applications (COCOA)

作者： Guo, Longkun Li, Min Xu, Dachuan Fuzhou Univ Coll Math & Comp Sci Fuzhou 350116 Peoples R China Shandong Normal Univ Sch Math & Stat Jinan 250014 Peoples R China Beijing Univ Technol Coll Appl Sci Beijing 100124 Peoples R China

ISBN: (纸本)9783319711478;9783319711461

In this paper, we study the maximum coverage problem with group budget constraints (MCG) that generalizes the maximum coverage problem. Given a ground set U in which i E U has a non-negative weight w,, a positive integer k and a collection of sets S, the maximum coverage problem is to pick k sets of S to maximize the total weight of their union. In MCG, S is partitioned into groups g1,, c and the goal is to pick k sets from S to maximize the total weight of their union, with at most ni E Z sets being picked from group ci. For MCG with n,/ = 1, Vi, we first present a factor 1 eapproximation algorithm which runs in exponential time. then we improve the runtime of the algorithm to 0 ( (m n q)3.5 L k3.5 q7 L) where 1,51 = m, =12, q is the number of groups, and L is the length of the input. the key idea of the improvement is to model selecting groups for MCG as computing a constrained flow in a corresponding auxiliary graph. It is also shown that the algorithm can be extended to solve MCG with general ni. Later, based on the main idea of partition we further improve the runtime of the algorithm to 0((m n q)3.5 L k(51.5 L), while compromise the approximation ratio to 1 e+-5-1, where (5 > 2 is any fixed integer. Consequently, we can balance approximation ratio and runtime of the algorithm by setting the value of S. this improves the previous best ratio of 0.5 on MCG due to Chekuri and Kumar [4].

关键词： Maximum coverage problem with group budget constraints Approximation algorithm Auxiliary graph Network flow Randomized linear programming rounding Partition

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Robust branch-and-cut-and-price for the capacitated vehicle routing problem

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10th international conference on integer programming and combinatorial optimization, IPCO 2004

作者： Fukasawa, Ricardo Lysgaard, Jens De Aragão, Marcus Poggi Reis, Marcelo Uchoa, Eduardo Werneck, Renato F. School of Industrial and Systems Engineering GeorgiaTech United States Department of Management Science and Logistics Aarhus School of Business Denmark Departamento de Informática PUC Rio de Janeiro Brazil Departamento de Engenharia de Produção Universidade Federal Fluminense Brazil Department of Computer Science Princeton University United States

ISBN: (纸本)3540221131

the best exact algorithms for the Capacitated Vehicle Routing Problem (CVRP) have been based on either branch-and-cut or Lagrangean relaxation/column generation. this paper presents an algorithm that combines both approaches: it works over the intersection of two polytopes, one associated with a traditional Lagrangean relaxation over q-routes, the other defined by bound, degree and capacity constraints. this is equivalent to a linear program with exponentially many variables and constraints that can lead to lower bounds that are superior to those given by previous methods. the resulting branch-andcut- and-price algorithm can solve to optimality all instances from the literature with up to 135 vertices. this doubles the size of the instances that can be consistently solved. © Springer-Verlag Berlin Heidelberg 2004.

关键词： integer programming

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