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15th international conference on Service Systems and Service Management (ICSSSM)

作者： Liu, Ming Liang, Bian Chu, Chengbin Chu, Feng Tongji Univ Sch Econ & Management Shanghai Peoples R China Univ Paris Saclay Cent Supelec Lab Genie Ind Chatenay Malabry France Univ Evry Val Essonne Lab IBISC Evry France

ISBN: (纸本)9781538651780

this paper studies the quayside operation problem, in which three seaside planning decisions are integrated, with the objective of minimizing the maximum relative tardiness. A refinement of the state-of-the-art formulation is presented in this work, and an improved exact combinatorial Benders decomposition algorithm is devised for the problem at container terminals which used to be typically modeled by mixed-integer linear programming problems containing a large number of "big-M" coefficients.

关键词： Quayside operation Mixed-integer programming combinatorial Benders Cuts

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Bi-objective orienteering: Towards a dynamic multi-objective evolutionary algorithm 10th

Bi-objective orienteering: Towards a dynamic multi-objective...

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10th international conference on Evolutionary Multi-Criterion optimization, EMO 2019

作者： Bossek, Jakob Grimme, Christian Meisel, Stephan Rudolph, Günter Trautmann, Heike Department of Information Systems University of Münster Leonardo-Campus 3 Münster48149 Germany Department of Computer Science TU Dortmund University Otto-Hahn-Str. 14 Dortmund44227 Germany

ISBN: (纸本)9783030125974

We tackle a bi-objective dynamic orienteering problem where customer requests arise as time passes by. the goal is to minimize the tour length traveled by a single delivery vehicle while simultaneously keeping the number of dismissed dynamic customers to a minimum. We propose a dynamic Evolutionary Multi-Objective Algorithm which is grounded on insights gained from a previous series of work on an a-posteriori version of the problem, where all request times are known in advance. In our experiments, we simulate different decision maker strategies and evaluate the development of the Pareto-front approximations on exemplary problem instances. It turns out, that despite severely reduced computational budget and no oracle-knowledge of request times the dynamic EMOA is capable of producing approximations which partially dominate the results of the a-posteriori EMOA and dynamic integer linear programming strategies. © Springer Nature Switzerland AG 2019.

关键词： combinatorial optimization

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18th international conference on integer programming and combinatorial optimization, IPCO 2016

18th International Conference on Integer Programming and Com...

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18th international conference on integer programming and combinatorial optimization, IPCO 2016

ISBN: (纸本)9783319334608

the proceedings contain 33 papers. the special focus in this conference is on integer programming and combinatorial optimization. the topics include: On approximation algorithms for concave mixed-integer quadratic programming;a link between optimization and convex geometry;rescaled coordinate descent methods for linear programming;approximating min-cost chain-constrained spanning trees;max-cut under graph constraints;sparsest cut in planar graphs, maximum concurrent flows and their connections with the max-cut problem;intersection cuts for bilevel optimization;exact algorithms for the chance-constrained vehicle routing problem;extended formulations in mixed-integer convex programming;popular edges and dominant matchings;semidefinite and linear programming integrality gaps for scheduling identical machines;stabilizing network bargaining games by blocking players;round-robin tournaments generated by the circle method have maximum carry-over;extreme functions with an arbitrary number of slopes;minimal cut-generating functions are nearly extreme;on the mixed binary representability of ellipsoidal regions;constant factor approximation for ATSP with two edge weights;improved approximation algorithms for hitting 3-vertex paths;improved approximations for cubic bipartite and cubic TSP;valid inequalities for separable concave constraints with indicator variables;a polyhedral approach to online bipartite matching;robust monotone submodular function maximization;maximizing monotone submodular functions over the integer lattice;submodular unsplittable flow on trees;strong reductions for extended formulations;sum-of-squares hierarchy lower bounds for symmetric formulations;approximation-friendly discrepancy rounding and on the quantile cut closure of chance-constrained problems.

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optimization in the construction of nearly cardinal and nearly symmetric wavelets

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

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international conference on Sampling theory and Applications (SampTA)

作者： Neil D. Dizon Jeffrey A. Hogan Joseph D. Lakey School of Maths and Phys Sci University of Newcastle Callaghan NSW Australia Department of Mathematical Sciences New Mexico State University Las Cruces NM USA

ISBN: (数字)9781728137414

ISBN: (纸本)9781728137421

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： Multiresolution analysis optimization Wavelet transforms Linear programming Mirrors

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An Efficient Heuristic for Pooled Repair Shop Designs 7th

An Efficient Heuristic for Pooled Repair Shop Designs

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7th international conference on Operations Research and Enterprise Systems, ICORES 2018

作者： Turan, Hasan Hüseyin Pokharel, Shaligram ElMekkawy, Tarek Y. Sleptchenko, Andrei Al-Khatib, Maryam Capability Systems Centre School of Engineering and Information Technology University of New South Wales Canberra Australia Department of Mechanical and Industrial Engineering College of Engineering Qatar University Doha Qatar Department of Industrial and Systems Engineering Khalifa University of Science and Technology Abu Dhabi United Arab Emirates

ISBN: (纸本)9783030160340

An effective spare part supply system planning is essential to achieve a high capital asset availability. We investigate the design problem of a repair shop in a single echelon repairable multi-item spare parts supply system. the repair shop usually consists of several servers with different skill sets. Once a failure occurs in the system, the failed part is queued to be served by a suitable server that has the required skill. We model the repair shop as a collection of independent sub-systems, where each sub-system is responsible for repairing certain types of failed parts. the procedure of partitioning a repair shop into sub-systems is known as pooling, and the repair shop formed by the union of independent sub-systems is called a pooled repair shop. Identifying the best partition is a challenging combinatorial optimization problem. In this direction, we formulate the problem as a stochastic nonlinear integer programming model and propose a sequential solution heuristic to find the best-pooled design by considering inventory allocation and capacity level designation of the repair shop. We conduct numerical experiments to quantify the value of the pooled repair shop designs. Our analysis shows that pooled designs can yield cost reductions by 25% to 45% compared to full flexible and dedicated designs. the proposed heuristic also achieves a lower average total system cost than that generated by a Genetic Algorithm (GA)-based solution algorithm. © 2019, Springer Nature Switzerland AG.

关键词： combinatorial optimization

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Identification methods of critical combination of vulnerable links in transportation networks 8th

Identification methods of critical combination of vulnerable...

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8th international conference on Green Intelligent Transportation Systems and Safety, 2017

作者： Li, Lin Ma, Jie Li, Dawei Branch of Intelligent Equipment and Information Engineering ChangZhou Vocational Institute of Engineering ChangZhouJiangsu213164 China School of Transportation Southeast University Nanjing210096 China

ISBN: (纸本)9789811303012

this chapter presents two global optimization approaches for identifying the most critical combination of vulnerable links in a transportation network. the first approach is formulated with a bi-level framework. It can be applied to small-scale networks. the second proposed approach formulates this problem as a Mixed-integer Nonlinear programming (MINLP). We revised the [MINLP] into a nicer form [RMINLP] to simplify the vulnerability problem into a discrete Network Design Problem (DNDP), so that it can be solved by many existing algorithms for DNDPs, and expand its scope of application. A numerical example of Sioux-Falls network is used to illustrate the two proposed approaches. the test results show that both approaches can provide a global optimization solution, while the second approach has a better property in computing efficiency. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Global optimization

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On the Use of Equivalence Classes for Optimal and Sub-Optimal Bin Covering

On the Use of Equivalence Classes for Optimal and Sub-Optima...

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IEEE international conference on Automation Science and Engineering (CASE)

作者： Sabino Roselli Fredrik Hagebring Sarmad Riazi Martin Fabian Knut Åkesson Department of Electrical Engineering Chalmers University of Technology Göteborg Sweden

Bin covering is an important optimization problem in many industrial fields, such as packaging, recycling, and food processing. the problem concerns a set of items, each with its own value, that are to be collected into bins in such a way that the total value of each bin, as measured by the sum of its item values, is not lower than a target value. the optimization problem concerns maximizing the number of bins. this is a combinatorial NP-hard problem, for which true optimal solutions can only be calculated in specific cases, such as when restricted to a small number of items. To get around this problem, many suboptimal approaches exist. this paper describes a formulation of the bin covering that allows to find the true optimum for a rather large number of items, over 1000. Also presented is a suboptimal solution, which is compared to the true optimum and found to come within less than 10% of the optimum.

关键词： optimization Computational complexity Mixed integer linear programming Set theory NP-hard problem combinatorial mathematics

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Coordinated Earth Observation Task Scheduling Algorithm for Multiple Controlling Platforms 3rd

Coordinated Earth Observation Task Scheduling Algorithm for ...

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3rd international conference on Space Information Networks, SINC 2018

作者： Wu, Jiaxin Liu, Runzi Sheng, Min Li, Jiandong Chi, Kai Tian, Wanyong The State Key Lab of ISN Xidian University Xi’anShaanxi710071 China Electric Information Network Laboratory CETC the 20th Research Institute Xi’anShaanxi710068 China

ISBN: (纸本)9789811359361

In view of the current situation that different Earth Observation Satellite systems are independent in our country, which results in the failure to share resources and to cope with numerous emergency tasks effectively, the paper proposes a Multi-platform Distributed Coordinate Task Scheduling Algorithm (MDCTS Algorithm) via consensus ADMM (Alternating Direction Method of Multipliers). Firstly, the problem of maximizing the overall value of multi-platform is modelled as a mixed-integer linear programming problem. then, the global optimization problem is decomposed into the scheduling of each platform based on local information and public task price issued by collaborative center. On the basis, MDCTS Algorithm is proposed. the simulation results show that compared to existing algorithm, the value of local and public tasks achieved by MDCTS Algorithm is higher under the premise that the local tasks and resource information of each controlling platform do not have to be disclosed. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Global optimization

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Critical arcs detection in influence networks

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NETWORKS 2018年第4期71卷 412-431页

作者： Gillen, Colin P. Veremyev, Alexander Prokopyev, Oleg A. Pasiliao, Eduardo L. Univ Pittsburgh Ind Engn 1048 Benedum Hall Pittsburgh PA 15261 USA Univ Florida Ind & Syst Engn 303 Weil Hall Gainesville FL 32611 USA US Air Force Res Lab Munit Directorate Bldg 13 Eglin AFB FL 32542 USA

the influence class of network problems models the propagation of influence (an abstraction of cascading beliefs, behaviors, or physical phenomena) in a network. Such problems have applications in social networks, electrical networks, computer networks, viral spreading, and so on. these types of networks have also been studied through the lens of critical arcs detection;that is, which arcs (edges) are the most important for maintaining some property of the network (e.g., connectivity). We introduce a new class of problems at the intersection of these two models. Specifically, given a set of seed nodes and the linear threshold influence propagation model, our work proposes to determine which arcs (e.g., relationships in a social network or communication pathways in a telecommunication network) are most critical to the influence propagation process. We prove NP-hardness of the problem. Time-dependent and time-independent mixed-integer programming (MIP) models are introduced. Insights gleaned from MIP solutions leads to the development of an improved MIP-based exact algorithm rooted in the idea of diffusion expansion. A heuristic based upon a new centrality measure is also proposed, and computational results are presented. (c) 2017 Wiley Periodicals, Inc. NETWORKS, Vol. 71(4), 412-431 2018

关键词： critical elements detection influence networks mixed-integer programming

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optimization of Active Distribution Network Source-Grid-Load Interactive Operation 5

Optimization of Active Distribution Network Source-Grid-Load...

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5th IEEE international conference on Cloud Computing and Intelligence Systems (CCIS)

作者： Huo, Siyu Huang, Chongxin Nanjing Univ Posts & Telecommun Coll Automat Nanjing 210023 Jiangsu Peoples R China Nanjing Univ Posts & Telecommun Inst Adv Technol Nanjing 210003 Peoples R China

ISBN: (纸本)9781538660058

In order to reduce the loss and improve the operating efficiency, it is necessary to optimize the operating schedule for the sources, grids and loads of active distribution network (ADN). Firstly, an operation model is established for source-grid-load interactive operation of ADN. In this model, the minimum loss is treated as the objective function, and the distributed generation sources, the tie-line switches of the grid, and the controllable loads serve as the optimized variables. Considering that the established model is about mix-integer nonlinear programming (MINTY) problem, the model is transformed into a bi-level combinatorial optimization problem to simplify the solving process. Finally, numerical tests are performed on the IEEE 33-node distribution network system, and results show that the proposed optimization method for the source-grid-load interactive operation of ADN can reduce the power loss and raise the operational efficiency.

关键词： Source-grid-load interactive operation Active distribution network Distributed generation Mix-integer nonlinear programming Controllable load

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