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

共 744 条记录，以下是171-180 订阅

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RFID Network Planning for Flexible Manufacturing Workshop with Multiple Coverage Requirements 8

RFID Network Planning for Flexible Manufacturing Workshop wi...

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8th IEEE international conference on Computer Science and Network Technology (ICCSNT)

作者： Wu, Lihui Ren, Junfei Li, Yuansheng Dai, Zhengzheng Zhang, Zhongwei Wu, Zhaoyun Henan Univ Technol Sch Mech & Elect Engn Zhengzhou Peoples R China

ISBN: (纸本)9781728181233

Flexible manufacturing workshops (FMWs) are important part of modern manufacturing enterprises. An optimized layout of radio frequency identifications (RFIDs) in an FMW is of great significance to improve information perception quality and reduce RFID deployment cost. therefore, the RFID network planning for an FMW is studied in this paper. Firstly, three common coverage requirements are analyzed, and a RFID reader radiation model and an FMW discrete grids model are constructed. Secondly, a 0-1 integer programming-based RFID network planning model is established with the optimization objectives of the RFID deployment cost, reader interference, and reading efficiency. thirdly, a hierarchical clustering and gradient descent-based network planning approach is proposed to solve the network planning model. An FMW case in a flexible manufacturing enterprise is taken to verify the RFID network planning model and the hierarchical clustering approach. the results show that the proposed model and approach are effective.

关键词： Flexible manufacturing workshop multiple coverage requirements RFID network planning integer programming multi-objective optimization

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A Simple Dual-RAMP Algorithm for the Capacitated Facility Location Problem 13th

A Simple Dual-RAMP Algorithm for the Capacitated Facility Lo...

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13th international conference on Learning and Intelligent optimization (LION)

作者： Matos, Telmo Oliveira, Oscar Gamboa, Dorabela Polytech Porto Sch Technol & Management CIICESI Ctr Res & Innovat Business Sci & Informat Porto Portugal

ISBN: (纸本)9783030386290;9783030386283

Facility Location embodies a class of problems concerned with locating a set of facilities to serve a geographically distributed population of customers at minimum cost. We address the classical Capacitated Facility Location Problem (CFLP) in which the assignment of facilities to customers must ensure enough facility capacity and all the customers must be served. this is a well-known NP-hard problem in combinatorial optimization that has been extensively studied in the literature. Due to the difficulty of the problem, significant research efforts have been devoted to developing advanced heuristic methods aimed at finding high-quality solutions in reasonable computational times. We propose a Relaxation AdaptiveMemory programming (RAMP) approach for the CFLP. Our method combines lagrangean subgradient search with an improvement method to explore primal-dual relationships to create advanced memory structures that integrate information from both primal and dual solution spaces. the algorithm was tested on the standard ORLIB dataset and on other very large-scale instances for the CFLP. Our approach efficiently found the optimal solution for all ORLIB instances and very competitive results for the large-scale ones. Comparisons with current best-performing algorithms for the CFLP show that our RAMP algorithm exhibits excellent results.

关键词： RAMP Facility Location Adaptive memory programming Lagrangean Relaxation

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Minimum Cycle Partition with Length Requirements 17th

Minimum Cycle Partition with Length Requirements

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17th international conference on the Integration of Constraint programming, Artificial Intelligence, and Operations Research (CPAIOR)

作者： Hoppmann, Kai Mexi, Gioni Burdakov, Oleg Casselgren, Carl Johan Koch, thorsten Zuse Inst Berlin Takustr 7 D-14195 Berlin Germany TU Berlin Chair Software & Algorithms Discrete Optimizat Str 17 Juni 135 D-106230 Berlin Germany Linkoping Univ Dept Math S-58183 Linkoping Sweden

ISBN: (纸本)9783030589424;9783030589417

In this article we introduce a Minimum Cycle Partition Problem with Length Requirements (CPLR). this generalization of the Travelling Salesman Problem (TSP) originates from routing Unmanned Aerial Vehicles (UAVs). Apart from nonnegative edge weights, CPLR has an individual critical weight value associated with each vertex. A cycle partition, i.e., a vertex disjoint cycle cover, is regarded as a feasible solution if the length of each cycle, which is the sum of the weights of its edges, is not greater than the critical weight of each of its vertices. the goal is to find a feasible partition, which minimizes the number of cycles. In this article, a heuristic algorithm is presented together with a Mixed integer programming (MIP) formulation of CPLR. We furthermore introduce a conflict graph, whose cliques yield valid constraints for the MIP model. Finally, we report on computational experiments conducted on TSPLIB-based test instances.

关键词： Travelling salesman problem combinatorial optimization Mixed integer linear programming Conflict graph Unmanned Aerial Vehicles

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Using integer programming to Search for Counterexamples: A Case Study 19th

Using Integer Programming to Search for Counterexamples: A C...

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19th international conference on Mathematical optimization theory and Operations Research, MOTOR 2020

作者： Lancia, Giuseppe Pippia, Eleonora Rinaldi, Franca Dipartimento di Scienze Matematiche Informatiche e Fisiche University of Udine Via delle Scienze 206 Udine33100 Italy The Research Hub by Electrolux Professional Viale Treviso 15 PordenonePN33170 Italy

ISBN: (纸本)9783030499877

It is known that there exist 4-regular, 1-tough graphs which are non-hamiltonian. the smallest such graph known has$$n=18$$ nodes and was found by Bauer et al., who conjectured that all 4-regular, 1-tough graphs with$$n\le 17$$ are hamiltonian. they in fact proved that this is true for$$n\le 15$$, but left open the possibility of non-hamiltonian graphs of 16 or 17 nodes. By using ILP for modeling a counterexample, and then finding out that the model has no solutions, we give an algorithmic proof that their conjecture was indeed correct. © 2020, Springer Nature Switzerland AG.

关键词： integer programming

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Robust optimization of Flow Shop Scheduling with Uncertain Processing Time 17

Robust optimization of Flow Shop Scheduling with Uncertain P...

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17th IEEE international conference on Mechatronics and Automation, ICMA 2020

作者： Sun, Qi Dou, Jianping Zhang, Canran Southeast University School of Mechanical Engineering Nanjing Jiangsu Province China Engineering Research Center of New Light Sources Technology and Equipment Ministry of Education Nanjing Jiangsu Province China

ISBN: (纸本)9781728164151

the flow shop scheduling (FSS) problem is a classic NP-hard combinatorial problem. Owing to the processing time of an operation is usually uncertain in practice, a scenario-based robust optimization model is established for the FSS problem with uncertain processing time. the optimization goal of this model is to minimize the combination of expected processing time and the deviation of makespan for all scenarios. then, a mixed integer linear programming (MILP) model is derived to minimize the objective, and two more constraints are added to ensure the validation of the model. Based on this model, the global best solutions of the small sized cases are obtained by LINGO. To solve the mid-to-large sized cases, a new algorithm called master-apprentice evolutionary algorithm (MAE) is adopted. the comparison between MAE and state-of-the-art metaheuristics illustrates the effectiveness of the MAE. © 2020 IEEE.

关键词： Evolutionary algorithms

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19th international conference on integer programming and combinatorial optimization, IPCO 2017

19th International Conference on Integer Programming and Com...

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19th international conference on integer programming and combinatorial optimization, IPCO 2017

ISBN: (纸本)9783319592497

the proceedings contain 36 papers. the special focus in this conference is on integer programming and combinatorial optimization. the topics include: On scheduling coflows;integrality gaps of integer knapsack problems;approximation of corner polyhedra with families of intersection cuts;the structure of the infinite models in integer programming;mixed-integer linear representability, disjunctions, and variable elimination;cutting planes from wide split disjunctions;the heterogeneous capacitated k-center problem;local guarantees in graph cuts and clustering;verifying integer programming results;long term behavior of dynamic equilibria in fluid queuing networks;approximation algorithm for the maximum traveling salesman problem;minimizing multimodular functions and allocating capacity in bike-sharing systems;stochastic online scheduling on unrelated machines;beating half for random arrival;an improved deterministic rescaling for linear programming algorithms;a quasi-polynomial approximation for the restricted assignment problem;adaptive submodular ranking;minimum birkhoff-von Neumann decomposition;maximum matching in the online batch-arrival model;budget feasible mechanisms on matroids;deterministic discrepancy minimization via the multiplicative weight update method;mixed-integer convex representability;high degree sum of squares proofs, bienstock-zuckerberg hierarchy and cg cuts;enumeration of integer points in projections of unbounded polyhedra and equilibrium computation in atomic splittable singleton congestion games.

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Computation Task Scheduling and Offloading optimization for Collaborative Mobile Edge Computing 26

Computation Task Scheduling and Offloading Optimization for ...

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26th IEEE international conference on Parallel and Distributed Systems (IEEE ICPADS)

作者： Lin, Bin Lin, Xiaohui Zhang, Shengli Wang, Hui Bi, Suzhi Shenzhen Univ Coll Elect & Informat Engn Shenzhen 518060 Peoples R China Peng Cheng Lab Shenzhen 518066 Peoples R China

ISBN: (纸本)9781728190747

Mobile edge computing (MEC) platform allows its subscribers to utilize computational resource in close proximity to reduce the computation latency. In this paper, we consider two users each has a set of computation tasks to execute. In particular, one user is a registered subscriber that can access the computation service of MEC platform, while the other unregistered user cannot directly access the MEC service. In this case, we allow the registered user to receive computation offloading from the unregistered user, compute the received task(s) locally or further offload to the MEC platform, and charge a fee that is proportional to the computation workload. We study from the registered user's perspective to maximize its total utility that balances the monetary income and the cost on execution delay and energy consumption. We formulate a mixed integer non-linear programming (MINLP) problem that jointly decides the execution scheduling of the computation tasks (i.e., the device where each task is executed) and the computation/communication resource allocation. To tackle the problem, we first derive the closed-form solution of the optimal resource allocation given the integer task scheduling decisions. We then propose a reduced-complexity approximate algorithm to optimize the combinatorial computation scheduling decisions. Simulation results show that the proposed collaborative computation scheme effectively improves the utility of the helper user compared with other benchmark methods, and the proposed solution method approaches the optimal solution within 0.1% average performance gap with significantly reduced complexity.

关键词： Mobile edge computing resource allocation user cooperation convex optimization

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Two Reformulation Approaches to Maximum-A-Posteriori Inference in Sum-Product Networks 10

Two Reformulation Approaches to Maximum-A-Posteriori Inferen...

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10th international conference on Probabilistic Graphical Models (PGM)

作者： Maua, Denis Deratani Ribeiro, Heitor Reis Katague, Gustavo Perez Antonucci, Alessandro Univ Sao Paulo Inst Math & Stat Sao Paulo Brazil Ist Dalle Molle Studi Intelligenza Artificiale Lugano Switzerland

Sum-product networks are expressive efficient probabilistic graphical models that allow for tractable marginal inference. Many tasks however require the computation of maximum-a-posteriori configurations, an NP-hard problem for such models. To date there have been very few proposals for computing maximum-a-posteriori configurations in sum-product networks. this is in sharp difference with other probabilistic frameworks such as Bayesian networks and random Markov fields, where the problem is also NP-hard. In this work we propose two approaches to reformulate maximuma-posteriori inference as other combinatorial optimization problems with widely available solvers. the first approach casts the problem as a similar inference problem in Bayesian networks, overcoming some limitations of previous similar translations. In addition to making available the toolset of maximum-a-posteriori inference on Bayesian networks to sum-product networks, our reformulation also provides further insight into the connections of these two classes of models. the second approach casts the problem as a mixed-integer linear program, for which there exists very efficient solvers. this allows such inferences to be enriched with integer-linear constraints, increasing the expressivity of the models. We compare our reformulation approaches in a large collection of problems, and against state-of-the-art approaches. the results show that reformulation approaches are competitive.

关键词： Tractable Probabilistic Models Sum-Product Networks Probabilistic Circuits Maximuma-Posteriori Inference Mixed-integer Linear programming Bayesian Networks

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Efficient Traffic Coordination Strategies at Intersections Using Multiple Collision Sets

Efficient Traffic Coordination Strategies at Intersections U...

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7th international conference on Communications, Signal Processing, and Systems (CSPS)

作者： Mo, Yangan Wang, Mengqi Zhang, Tingting Xu, Hongguang Harbin Inst Technol Shenzhen Grad Sch Commun Engn Res Ctr Shenzhen Peoples R China

ISBN: (纸本)9789811365089;9789811365072

Appropriate traffic coordination at intersections where multiple roads merge plays an important role in modern intelligent transportations systems. In this paper, we try to propose an efficient traffic coordination framework using multiple collision sets. Aiming at the essentially non-convex problem, we try to reformulate the original problem into a mixed binary integer quadratic programming one by proper relaxations. Low complexity solutions are also given afterwards. Numeric results show that the traffic throughput at intersections can be significantly improved compared to the existing investigations.

关键词： Intelligent transportations Intersection coordination Traffic optimization Mixed binary integer programming

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optimization in the construction of nearly cardinal and nearly symmetric wavelets 13

Optimization in the construction of nearly cardinal and near...

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13th international conference on Sampling theory and Applications (SampTA)

作者： Dizon, Neil D. Hogan, Jeffrey A. Lakey, Joseph D. Univ Newcastle Sch Maths & Phys Sci Callaghan NSW 2308 Australia New Mexico State Univ Dept Math Sci Las Cruces NM 88003 USA

ISBN: (纸本)9781728137414

We present two approaches to the construction of scaling functions and wavelets that generate nearly cardinal and nearly symmetric wavelets on the line. the first approach casts wavelet construction as an optimization problem by imposing constraints on the integer samples of the scaling function and its associated wavelet and with an objective function that minimizes deviation from cardinality or symmetry. the second method is an extension of the feasibility approach by Franklin, Hogan, and Tam to allow for symmetry by considering variables generated from uniform samples of the quadrature mirror filter, and is solved via the Douglas-Rachford algorithm.

关键词： integer programming

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