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A Note on Convex Reformulation Schemes for mixed integer Quadratic Programs

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 2014年第2期160卷 457-469页

作者： Newby, Eric Ali, M. M. Univ Witwatersrand Sch Computat & Appl Math ZA-2050 Johannesburg South Africa

This paper examines a convex reformulation scheme for mixed integer quadratic programs, which was recently developed in the literature. A modification to the scheme, based on a linear transformation, is presented. The modification improves performance for problems which have more continuous variables than integer variables. Numerical results are presented showing the effectiveness of the modification.

关键词： mixed integer programming Quadratic programming Linear transformation Non-convex optimization Semidefinite programming

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Staff rostering in call centers providing employee transportation

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OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2014年 43卷 41-53页

作者： Ormeci, E. Lerzan Salman, F. Sibel Yucel, Eda Koc Univ Coll Engn Dept Ind Engn Istanbul Turkey

We address the staff rostering problem in call centers with the goal of balancing operational cost, agent satisfaction and customer service objectives. In metropolitan cities such as Istanbul and Mumbai, call centers provide the transportation of their staff so that shuttle costs constitute a significant part of the operational costs. We develop a mixed integer programming model that incorporates the shuttle requirements at the beginning and end of the shifts into the agent-shift assignment decisions, while considering the skill sets of the agents, and other constraints due to workforce regulations and agent preferences. We analyze model solutions for a banking call center under various management priorities to understand the interactions among the conflicting objectives. We show that considering transportation costs as well as agent preferences in agent-shift assignments provides significant benefits in terms of both cost savings and employee satisfaction. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Call center operations Workforce scheduling Rostering Pick-and-drop services Agent satisfaction mixed integer programming

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A decision-making framework for justifying a portfolio of IT projects

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INTERNATIONAL JOURNAL OF PROJECT MANAGEMENT 2014年第4期32卷 625-639页

作者： Pendharkar, Parag C. Penn State Univ Harrisburg Sch Business Adm Middletown PA 17057 USA

This paper presents a comprehensive decision-making framework for evaluating a portfolio of IT projects. A problem of IT project selection with and without project interdependencies is considered. The problem is subject to maximum project funding budget constraint. When IT project portfolio contains independent projects, a dynamic programming (DP) solution procedure is proposed to efficiently solve the portfolio of IT projects' problem. However, when IT project portfolio contains project interdependencies, a mixed integer programming (MIP) approach is needed to solve the problem optimally. Experiments and results using simulated data using Monte Carlo simulation are provided. The results indicate that a large set of project selection problems containing up to 60 projects can be solved easily using the proposed decision-making framework. (C) 2013 Elsevier Ltd. APM and IPMA. All rights reserved.

关键词： Dynamic programming mixed integer programming Real options

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LEAST QUANTILE REGRESSION VIA MODERN OPTIMIZATION

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ANNALS OF STATISTICS 2014年第6期42卷 2494-2525页

作者： Bertsimas, Dimitris Mazumder, Rahul MIT MIT Sloan Sch Management Cambridge MA 02139 USA MIT Operat Res Ctr Cambridge MA 02139 USA Columbia Univ Dept Stat New York NY 10027 USA

We address the Least Quantile of Squares (LQS) (and in particular the Least Median of Squares) regression problem using modern optimization methods. We propose a mixed integer Optimization (MIO) formulation of the LQS problem which allows us to find a provably global optimal solution for the LQS problem. Our MIO framework has the appealing characteristic that if we terminate the algorithm early, we obtain a solution with a guarantee on its sub-optimality. We also propose continuous optimization methods based on first-order subdifferential methods, sequential linear optimization and hybrid combinations of them to obtain near optimal solutions to the LQS problem. The MIO algorithm is found to benefit significantly from high quality solutions delivered by our continuous optimization based methods. We further show that the MIO approach leads to (a) an optimal solution for any dataset, where the data-points (y(i), x(i))'s are not necessarily in general position, (b) a simple proof of the breakdown point of the LQS objective value that holds for any dataset and (c) an extension to situations where there are polyhedral constraints on the regression coefficient vector. We report computational results with both synthetic and real-world datasets showing that the MIO algorithm with warm starts from the continuous optimization methods solve small (n = 100) and medium (n = 500) size problems to provable optimality in under two hours, and outperform all publicly available methods for large-scale (n = 10,000) LQS problems.

关键词： Least median of squares robust statistics least quantile regression algorithms mixed integer programming global optimization continuous optimization

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An adaptive genetic algorithm for the time dependent inventory routing problem

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JOURNAL OF INTELLIGENT MANUFACTURING 2014年第5期25卷 1025-1042页

作者： Cho, Dong Won Lee, Young Hae Lee, Tae Youn Gen, Mitsuo Hanyang Univ Dept Ind & Management Engn Ansan 426791 Gyeonggi Do South Korea Fuzzy Log Syst Inst Iizuka Fukuoka Japan

In this paper we propose an adaptive genetic algorithm that produces good quality solutions to the time dependent inventory routing problem (TDIRP) in which inventory control and time dependent vehicle routing decisions for a set of retailers are made simultaneously over a specific planning horizon. This work is motivated by the effect of dynamic traffic conditions in an urban context and the resulting inventory and transportation costs. We provide a mixed integer programming formulation for TDIRP. Since finding the optimal solutions for TDIRP is a NP-hard problem, an adaptive genetic algorithm is applied. We develop new genetic representation and design suitable crossover and mutation operators for the improvement phase. We use adaptive genetic operator proposed by Yun and Gen (Fuzzy Optim Decis Mak 2(2):161-175, 2003) for the automatic setting of the genetic parameter values. The comparison of results shows the significance of the designed AGA and demonstrates the capability of reaching solutions within 0.5 % of the optimum on sets of test problems.

关键词： Time dependent inventory routing problem Adaptive genetic algorithm mixed integer programming

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Alternative MIP formulations for an integrated shift scheduling and task assignment problem

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DISCRETE APPLIED MATHEMATICS 2014年 164卷 328-343页

作者： Telhada, Joao Univ Lisbon Ctr Invest Operac P-1699 Lisbon Portugal

A problem of personnel scheduling in a multiskilled environment is addressed. This problem is treated in an integrated manner, modelling shift scheduling and task assignment as one problem. Additionally, the integrated approach allows also to better model intraday breaks and days-off scheduling. Alternative MIP formulations are presented which lead to optimal shift schedulings and task assignments. Improved models are obtained by deriving new block indexed and position indexed variables. Computational results show the improvement obtained by extended formulations. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Personnel scheduling mixed integer programming LP reformulations Shift scheduling Task assignment

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Day Ahead Schedule of Remote Microgrids with Renewable Energy Sources Considering Battery Lifetime 11

Day Ahead Schedule of Remote Microgrids with Renewable Energ...

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11th IEEE/IAS International Conference on Industry Applications (IEEE INDUSCON)

作者： Chalise, Santosh Tonkoski, Reinaldo South Dakota State Univ Brookings SD 57007 USA

ISBN: (纸本)9781479955510

Remote microgrids are a viable option for electrification where the main grid expansion is either impossible or not economical. Typically, remote microgrid consists of diesel generator as a primary source of energy which has a high fuel cost. Renewable energy sources can be used to reduce the fuel consumption with proper coordination and scheduling methods. Storage devices, usually battery, used in remote microgrid are expensive and toxic in nature;therefore battery lifetime is another important parameter to be considered during microgrid scheduling. In this paper, four test cases were developed for the study of fuel consumption. Problems were formulated as mixed integer programming (MIP) and solved using GAMS/CPLEX 12.6 solver. Furthermore, the battery lifetime model was included in the optimization model and fuel consumption was compared with other cases. Results show the slight increment in fuel consumption when the battery lifetime model was included.

关键词： Battery life microgrid mixed integer programming multiobjective optimization photovoltaic renewable energy

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Advanced optimization methods for power systems

Advanced optimization methods for power systems

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2014 Power Systems Computation Conference (PSCC)

作者： Panciatici, P. Campi, M. C. Garatti, S. Low, S. H. Molzahn, D. K. Sun, A. X. Wehenkel, L. RTE R&D Dept Versailles France Univ Brescia Dept Informat Engn Brescia Italy Politecn Milan Dept Elect Comp Sci & Bioengn Milan Italy CALTECH Div Engn & Appl Sci Pasadena CA 91125 USA Univ Michigan Dept EE&CS Ann Arbor MI 48109 USA Georgia Inst Technol H Milton Stewart Sch Ind & Syst Engn Atlanta GA 30332 USA Univ Liege Dept EE&CS Inst Montefiore B-4000 Liege Belgium

ISBN: (纸本)9788393580132

Power system planning and operation offers multitudinous opportunities for optimization methods. In practice, these problems are generally large-scale, non-linear, subject to uncertainties, and combine both continuous and discrete variables. In the recent years, a number of complementary theoretical advances in addressing such problems have been obtained in the field of applied mathematics. The paper introduces a selection of these advances in the fields of non-convex optimization, in mixed-integer programming, and in optimization under uncertainty. The practical relevance of these developments for power systems planning and operation are discussed, and the opportunities for combining them, together with high-performance computing and big data infrastructures, as well as novel machine learning and randomized algorithms, are highlighted.

关键词： Big Data concave programming integer programming learning (artificial intelligence) nonlinear programming parallel processing power engineering computing power system planning randomised algorithms Big Data infrastructure advanced optimization method high-performance computing machine learning mixed integer programming nonconvex optimization power system operation randomized algorithm Electronic mail Europe Linear programming Optimization Planning Power systems Uncertainty Power system planning randomized algorithms integer programming power systems High Performance Computing big data Power engineering computing electronic mail Nonlinear programming PARALLEL PROCESSING (COMPUTERS) Optimization methods linear programming Uncertainty

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Combined Calculation of Optimal Routing and Bandwidth Allocation in Energy Aware Networks 26

Combined Calculation of Optimal Routing and Bandwidth Alloca...

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26th International Teletraffic Congress (ITC)

作者： Jaskola, Przemyslaw Arabas, Piotr Karbowski, Andrzej Naukowa & Akad Siec Komputerowa Inst Badawczy Ul Wawozowa 18 PL-02796 Warsaw Poland Politech Warszawskiej Inst Automatyki & Informatyki Stosowanej PL-00665 Warsaw Poland

ISBN: (纸本)9780983628392

Efforts to reduce power consumption in telecommunication networks follow in two mutually related directions - design of a more efficient equipment and development of energy-aware network control strategies and protocols. The paper presents a formulation of two-criteria traffic engineering problem, which takes advantage of energy saving capabilities in software routers. The first optimization criterion is the energy consumption, and the second one is the quality of service and service sustainability. Models and traffic engineering strategy were verified in laboratory experiments.

关键词： network optimization green networking nonlinear programming mixed integer programming

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Integrated Approach for Flexible mixed Model Assembly Lines Balancing and Model Sequencing Problem 4

Integrated Approach for Flexible Mixed Model Assembly Lines ...

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4th International Conference on Applied Mechanics, Materials and Manufacturing (ICAMMM)

作者： Nie, Li Bai, Yuewei Wu, Jun Pang, Changtao Shanghai Second Polytech Univ Sch Mech & Elect Engn Shanghai Peoples R China Beijing Aviat Key Lab Sci & Technol Precis Mfg Beijing Peoples R China

ISBN: (纸本)9783038352884

The manufacturers nowadays are forced to respond very quickly to changes in the market conditions. To adopt flexible mixed model assembly lines (MMAL) is a preferred way for manufacturers to improve competitiveness. Managing a mixed model assembly line involves two problems: assigning assembly tasks to stations (balancing problem) and determining the sequence of products at each station (sequencing problem). In order to solve both balancing and sequencing problem in MMAL simultaneously, an integrated mathematical model based on mixed integer programming (MIP) is developed to describe the problem. In the model, general type precedence relations and task duplications are considered. Due to the NP-hardness of the balancing and sequencing problem of MMAL, GA is designed to search the optimal solution. The efficiency of the GA is demonstrated by a case study.

关键词： mixed model assembly lines Balancing Sequencing mixed integer programming Genetic Algorithm

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