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Genetic and Evolutionary Computation Conference (GECCO)

作者： Kenny, Angus Li, Xiaodong Ernst, Andreas T. RMIT Univ Sch Sci Melbourne Vic Australia Monash Univ Sch Math Sci Clayton Vic Australia

ISBN: (纸本)9781450356183

Many large-scale combinatorial problems contain too many variables and constraints for conventional mixed-integer programming (MIP) solvers to manage. To make the problems easier for the solvers to handle, various meta-heuristic techniques can be applied to reduce the size of the search space, by removing, or aggregating, variables and constraints. A novel meta-heuristic technique is presented in this paper called merge search, which takes an initial solution and uses the information from a large population of neighbouring solutions to determine promising areas of the search space to focus on. The population is merged to produce a restricted sub-problem, with far fewer variables and constraints, which can then be solved by a MIP solver. Merge search is applied to a complex problem from open-pit mining called the constrained pit (CPIT) problem, and compared to current state-of-the-art results on well known benchmark problems minelib [7] and is shown to give better quality solutions in five of the six instances.

关键词： Applied computing Hybrid algorithms mixed integer programming Merge search Mine planning

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Demonstrating Scalability and Efficiency of Pack-Centric Resource Management for Cloud 9

Demonstrating Scalability and Efficiency of Pack-Centric Res...

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9th IEEE International Conference on Cloud Computing (CLOUD)

作者： Wang, Yi Xia, Ye Chen, Shigang Tsugawa, Mauricio Fortes, Jose A. B. Univ Florida Dept Comp & Informat Sci & Engn Gainesville FL 32611 USA Univ Florida Dept Elect & Comp Engn Gainesville FL 32611 USA

ISBN: (纸本)9781509026197

Computational clouds have evolved to go beyond cost-effective on-demand hosting of IT resources and elasticity. The added features now include the ability to offer entire IT systems as a service that can quickly adapt to changing business environments. The new trend introduces challenges in datacenter resource management, including scalability, system-orientation, and optimization supporting both datacenter efficiency and customer system agility and performance. The conventional approach of resource management adopts a flat fine-grained model that results in problem formulations of enormous sizes;it also has the drawback of being less flexible in meeting customers' need. In this paper, we introduce a pack-centric approach to datacenter resource management by abstracting a system as a pack of resources and considering the mapping of these packs onto physical datacenter resource groups, called swads. The assignments of packs to swads are formulated as mixed integer programming problems. Scalability is achieved through a hierarchical decomposition method and parallel solvers. The new datacenter resource management framework is illustrated with a concrete resource placement problem. Numerical experiments show the scalability of the hierarchical decomposition method and the benefits of the overall framework.

关键词： Cloud Computing Datacenter Virtual Machine Placement Resource Management mixed integer programming

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Branch-and-Cut-and-Price for Capacitated Connected Facility Location

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Journal of Mathematical Modelling and Algorithms 2011年第3期10卷 245-267页

作者： Leitner, Markus Raidl, Günther R. Institute of Computer Graphics and Algorithms Vienna University of Technology Vienna Austria

We consider a generalization of the Connected Facility Location Problem (ConFL), suitable to model real world network extension scenarios such as fiber-to-the-curb. In addition to choosing a set of facilities and connecting them by a Steiner tree as in ConFL, we aim to maximize the resulting profit by potentially supplying only a subset of all customers. Furthermore, capacity constraints on potential facilities need to be considered. We present two mixed integer programming based approaches which are solved using branch-and-cut and branch-and-cut-and-price, respectively. By studying the corresponding polyhedra we analyze both approaches theoretically and show their advantages over previously presented models. Furthermore, using a computational study we are able to additionally show significant advantages of our models over previously presented ones from a practical point of view. © 2011 Springer Science+Business Media B.V.

关键词： Branch-and-cut Branch-and-cut-and-price Connected facility location mixed integer programming Network design

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Optimal wavelength allocation and flow assignment in multiwavelength optical networks

Optimal wavelength allocation and flow assignment in multiwa...

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IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM 2001)

作者： Kabranov, O Makrakis, D Charalambous, C Ionescu, D Univ Ottawa SITE Broadband Wireless & Internetworking Res Lab Ottawa ON K1N 6N5 Canada

ISBN: (纸本)0780370805

Automatically Switched Optical Networks (ASON) require a control strategy that determines the optimal distribution of flows over different wavelengths. Such strategy will increase the profit, by allowing service providers to quickly and effectively define and deploy new service offers. In this paper we introduce a demand elasticity based model for wavelength and flow assignment in multiwavelength optical networks. The model captures the appropriate optical flow for every link and for every wavelength using price/demand elasticity. The model assumes that the physical and logical topology of the optical network, the maintenance cost, and the traffic demands are known parameters. Under these assumptions a mixed integer optimization is used for wavelength allocation and flow assignment of the requested traffic demand and surplus maximization for the transport service supplier, operating the optical network. A case study shows how the bandwidth demand affects the supplier's profit.

关键词： wavelength allocation mixed integer programming demand elasticity

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Quantile forecast combination using stochastic dominance

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EMPIRICAL ECONOMICS 2018年第4期55卷 1717-1755页

作者： Pinar, Mehmet Stengos, Thanasis Yazgan, M. Ege Edge Hill Univ Business Sch St Helens Rd Ormskirk L39 4QP Lancs England Univ Guelph Dept Econ Guelph ON N1G 2W1 Canada Istanbul Bilgi Univ Dept Econ TR-34060 Istanbul Turkey

This paper derives optimal forecast combinations based on stochastic dominance efficiency (SDE) analysis with differential forecast weights for different quantiles of forecast error distribution. For the optimal forecast combination, SDE will minimize the cumulative density functions of the levels of loss at different quantiles of the forecast error distribution by combining different time-series model-based forecasts. Using two exchange rate series on weekly data for the Japanese yen/US dollar and US dollar/Great Britain pound, we find that the optimal forecast combinations with SDE weights perform better than different forecast selection and combination methods for the majority of the cases at different quantiles of the error distribution. However, there are also some very few cases where some other forecast selection and combination model performs equally well at some quantiles of the forecast error distribution. Different forecasting period and quadratic loss function are used to obtain optimal forecast combinations, and results are robust to these choices. The out-of-sample performance of the SDE forecast combinations is also better than that of the other forecast selection and combination models we considered.

关键词： Nonparametric stochastic dominance mixed integer programming Forecast combinations

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Quantification of Electricity Power Balance Based on Optimisation of Time-series Combinations of Multiple Types of Resources 21

Quantification of Electricity Power Balance Based on Optimis...

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21st International Conference on Harmonics and Quality of Power

作者： Zhou, Yongjun Liu, Fu Lobo, Tsering Chen, Silin Zhao, Qinghua Zhang, Shu State Grid Tibet Elect Power Co Tibet Beijing Peoples R China Sichuan Univ Chengdu Peoples R China

ISBN: (纸本)9798350382570;9798350382563

As renewable energy generation expands, the challenge of power equilibrium in the evolving power system intensifies. Integrating flexible loads into the regional grid's power balance management contributes to resolving issues related to renewable energy consumption and curtailment of wind and solar output. This study intricately models thermal power stations, diverse hydroelectric facilities, and flexible loads, establishing an optimization model that encompasses multiple resource types with the aim of minimizing the overall system operating cost. Through case study analysis, the effectiveness and financial viability of the proposed approach are demonstrated. Findings indicate that involving flexible loads in regional grid power balance significantly improves the region's capacity to absorb renewable energy and concurrently enhances economic efficiency.

关键词： Electricity power balance Flexibility load Refined modelling mixed integer programming

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Dynamic Fleet Management for Autonomous Vehicles: Learning- and optimization-based strategies

Dynamic Fleet Management for Autonomous Vehicles: Learning- ...

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作者： Alves Beirigo, B. Delft University of Technology

学位级别：博士

Autonomous vehicles (AVs) have been heralded as the key to unlock a shared mobility future where transportation is more efficient, convenient, and cheaper. However, the AV utopia can only come to fruition if the majority of users trust that autonomous mobility-on-demand (AMoD) systems are on a par with owning a vehicle in terms of service quality. Once the perception of quality is highly subjective, we propose a more personalized approach to on-demand mobility, in which users are segmented into service quality classes. These classes comprise minimum requirements regarding responsiveness and privacy, allowing us to model a series of user profiles formalized using strict service quality contracts. By honoring these contracts, providers can build users' trust and gain their loyalty, which on a grander scheme can contribute to a faster transition to a shared mobility *** thesis presents a series of strategies to guaranteeing service quality throughout operational scenarios arising in the timeline of AV technology deployment. First, a precondition to providing service quality in autonomous transportation is safety. During a transition phase to full automation, AV operation will likely be restricted to areas where safe operations are guaranteed, leading to the formation of hybrid street networks comprised of autonomous and non-autonomous vehicle zones. In this setting, meeting user service quality expectations is primarily a matter of coverage, once mobility services will have to access both AV-ready and not AV-ready areas. Accordingly, this thesis proposes solutions to overcome the challenges entailed by such a transition scenario, where infrastructures, regulatory measures, and AV technology are gradually ***, assuming that widespread automated driving is the new status quo, we set out to model rich autonomous transportation scenarios comprised of heterogeneous users and vehicles. Central to our analysis is finding an adequate tradeoff between fleet si

关键词： dynamic fleet management autonomous vehicles service quality on-demand hiring autonomous vehicle zone people and freight integration mobility poverty mobility-on-demand approximate dynamic programming matheuristic mixed integer programming

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Optimization Algorithms for Maritime Terminal and Fleet Management

Optimization Algorithms for Maritime Terminal and Fleet Mana...

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作者： Jose Fernando ALVAREZ Pompeu Fabra University

学位级别：博士

The vessel loading plan must comply with stowage instructions provided by the vessel operator, which specify characteristics of each container to be loaded. Additionally, the vessel loading plan should expedite transport operations in the yard. We present two vessel planning algorithms. In the first model, the vessel planning problem is formulated as a mixed integer programming (MIP) model and solved using Lagrangean relaxation and branch and bound. In the second model, a tabu metaheuristic is employed. Liner companies face a complex decision problem in determining the optimal fleet composition and routing. We present a model that captures the revenues and operating expenses of a liner company. The model allows for vessel types with different cost and operating properties; transhipment hubs; port delays; regional trade imbalances; and the possibility of rejecting transportation demand selectively. A case study explores the sensitivity of optimal fleet composition and routing to bunker costs

关键词： lagrangean decomposition mixed integer programming metaheuristicas transbordo programacion por enteros flotas maritimas decomposicion lagrangeana terminales maritimas reach stacker transhipment bunker fuel metaheuristics maritime fleet routing

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Size Ramsey numbers and integer programming

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Electronic Notes in Discrete Mathematics 2001年 10卷 242-244页

作者： Pikhurko, Oleg DPMMS Centre for Mathematical Sciences Cambridge University Cambridge CB3 0WB United Kingdom

We show that limn→∞ r̂(F1,n, . . . , Fq,n, Fp+1, . . . , Fr)/n exists, where the bipartite graphs Fq+1, . . . , Fr do not depend on n while, for 1 ≤ i ≤ q, Fi,n is obtained from some bipartite graph Fi with parts ... 详细信息

We show that lim_n→∞ r̂(F_1,n, . . . , F_q,n, F_p+1, . . . , F_r)/n exists, where the bipartite graphs F_q+1, . . . , F_r do not depend on n while, for 1 ≤ i ≤ q, F_i,n is obtained from some bipartite graph F_i with parts V₁ ∪ V₂ = V(F _i) by duplicating each vertex v ∈ V₂ (c_v + o(1))n times for some real c_v > 0. In fact, the limit is the minimum of a certain mixed integer program. Using the Farkas Lemma we compute it when each forbidden graph is a complete bipartite graph, in particular answering a question of Erdos, Faudree, Rousseau and Schelp (1978) who asked for the asymptotics of r̂(K_s,n, K_s,n,) for fixed s and large n. Furthermore, we prove (for all sufficiently large n) the conjecture of Faudree, Rousseau and Sheehan (1983) that r̂(K_2,n, K _2,n) = 18n - 15. Complete proofs can be found in [3].

关键词： Bipartite graphs Farkas Lemma mixed integer programming Size Ramsey number

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Optimal injection points for information diffusion

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ECONOMICS LETTERS 2019年 175卷 67-70页

作者： Rose, Christiern Univ Queensland Brisbane Qld Australia

The success of economic policy often hinges on the diffusion of information on its existence and nature through social networks. Informing all potential beneficiaries directly is costly, hence policymakers may prefer to inform a few key agents instead. Existing approaches typically select such injection points based on network centrality measures, and propose informing the most centrally located agents. This does not account for overlap in information diffusion, and can inhibit diffusion to the periphery. This note proposes a method to optimally select injection points accounting for overlap in information diffusion. The approach is based on that of Banerjee et al. (2013) and involves solving a mixed integer program. For large networks, a convex relaxation of the mixed integer program is more computationally tractable. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Social networks Information diffusion Network centrality mixed integer programming

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