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A mixed integer programming model to locate traumatic brain injury treatment units in the Department of Veterans Affairs: A case study

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Health Care Management Science 2007年第3期10卷 253-267页

作者： Côté, Murray J. Syam, Siddhartha S. Vogel, W. Bruce Cowper, Diane C. Department of Medicine Health Sciences Center University of Colorado at Denver Aurora CO 80045 United States Department of Management Marquette University Milwaukee WI 53201 United States VA Rehabilitation Outcomes Research Center Gainesville FL 32608 United States

For the Department of Veterans Affairs (VA), traumatic brain injury (TBI) is a significant problem facing active duty military personnel, veterans, their families, and caregivers. The VA has designated TBI treatment as one of its physical medicine and rehabilitation special emphasis programs, thereby providing a comprehensive array of treatment services to those military personnel and veterans with TBI. Timely treatment of TBI is critical in achieving maximal recovery, and being in geographical proximity to a medical center with specialized TBI treatment services is a major determinant of whether such treatment is utilized. We present a mixed integer programming model for locating TBI treatment units in the VA. This model was developed for the VA Rehabilitation Strategic Healthcare Group to assist in locating new TBI treatment units. The optimization model assigns TBI treatment units to existing VA medical centers while minimizing the sum of patient treatment costs, patient lodging and travel costs, and the penalty costs associated with foregone treatment revenue and excess capacity utilization. We demonstrate our model with VA TBI admission data from one of the VA's integrated service networks, and discuss the expected service and cost implications for a range of TBI treatment unit location options. © Springer Science+Business Media, LLC 2007.

关键词： Facility location and allocation Health care planning mixed integer programming Traumatic brain injury Veterans health

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Two mixed integer programming formulations on single machine to reschedule repaired jobs for minimizing the total waiting-time

Two mixed integer programming formulations on single machine...

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Chinese Automation Congress (CAC)

作者： Guo, Yandong Xie, Xiaodong Bohai Univ Sch Math & Phys Jinzhou 121013 Liaoning Peoples R China

ISBN: (纸本)9781538635247

In this paper, a rescheduling problem to insert new jobs into original schedule is studied. First, this rescheduling problem is reduced to the NP-hard problem. Then the rescheduling problem is formulated as two mixed integer programming (MIP) formulations, and solved by using CPLEX. Further, the computational performance is showed and analysised for two proposed different MIP.

关键词： Single Machine Rescheduling mixed integer programming Decision Variables

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Design optimization of distribution transformers based on mixed integer programming methodology

Design optimization of distribution transformers based on mi...

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5th Japanese-Mediterranean Workshop on Applied Electromagnetic Engineering for Magnetic, Superconductiong and Nano Materials

作者： Amoiralis, Eleftherios I. Georgilakis, Pavlos S. Tsili, Marina A. Tech Univ Crete Dept Prod Engn & Management GR-73100 Khania Greece Natl Tech Univ Athens Fac Elect & Comp Engn GR-15780 Athens Greece

In this paper, an effective optimization method is proposed with the aim of minimizing the active part cost of wound core distribution transformers, taking into account constraints imposed both by international specifications and customer needs. In order to achieve so, mixed integer programming in conjunction with the Branch and Bound technique are employed. The proposed methodology is compared with a heuristic optimization methodology of the transformer manufacturing industry and the results demonstrate the robustness and the superiority of this new approach.

关键词： Transformer design optimization methodology mixed integer programming branch and bound Optimization methods distribution transformer Wound core type transformer

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Optimal design of sensor parameters in PLC-based control system using mixed integer programming

Optimal design of sensor parameters in PLC-based control sys...

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17th Workshop on Circuits and Systems

作者： Konaka, E Mutou, T Suzuki, T Okuma, S Nagoya Univ Grad Sch Engn Nagoya Aichi 4648603 Japan

Programmable Logic Controller (PLC) has been widely used in the industrial control. Inherently, the PLC-based system is a class of Hybrid Dynamical System (HDS) in which continuous state of the plant is controlled by the discrete logic-based controller. This paper firstly presents the formal algebraic model of the PLC-based control systems which enable the designer to formulate the various kinds of optimization problem. Secondly, the optimization problem of the 'sensor parameters,' such as the location of the limit switch in the material handling system, the threshold temperature of the thermostat in the temperature control system, is addressed. Finally, we formulate this problem as mixed Logical Dynamical Systems (MLDS) form which enables us to optimize the sensor parameters by applying the mixed integer programming.

关键词： programmable logic controller sensor parameter optimization mixed integer programming

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Packing While Traveling: mixed integer programming for a Class of Nonlinear Knapsack Problems 12

Packing While Traveling: Mixed Integer Programming for a Cla...

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12th International Conference on Integration of Artificial Intelligence (AI) and Operations Research (OR) Techniques in Constraint programming (CPAIOR)

作者： Polyakovskiy, Sergey Neumann, Frank Univ Adelaide Sch Comp Sci Optimisat & Logist Adelaide SA Australia

ISBN: (纸本)9783319180083;9783319180076

Packing and vehicle routing problems play an important role in the area of supply chain management. In this paper, we introduce a non-linear knapsack problem that occurs when packing items along a fixed route and taking into account travel time. We investigate constrained and unconstrained versions of the problem and show that both are NP-hard. In order to solve the problems, we provide a pre-processing scheme as well as exact and approximate mixed integer programming (MIP) solutions. Our experimental results show the effectiveness of the MIP solutions and in particular point out that the approximate MIP approach often leads to near optimal results within far less computation time than the exact approach.

关键词： Non-linear knapsack problem NP-hardness mixed integer programming Linearization technique Approximation technique

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Modelling of bicycle manufacturing via multi-criteria mixed integer programming 12

Modelling of bicycle manufacturing via multi-criteria mixed ...

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12th Global Conference on Sustainable Manufacturing - Emerging Potentials

作者： Schenker, Sebastian Steingrimsson, Jon Gardar Borndoerfer, Ralf Seliger, Guenther Zuse Inst Berlin D-14195 Berlin Germany Dept Assembly Technol & Factory Management D-10587 Berlin Germany

Sustainable manufacturing considers the economic, environmental and social dimensions as equally important. For any product, like the common bicycles, a holistic view on the different life cycle phases has to be taken in order to ensure that resources are utilised adequately. Preferences on the three dimensions might lead to different selections of materials, used equipment or required education for fulfilling the considered objectives. In a first approach, bicycle manufacturing alternatives are identified and modelled via bi-criteria mixed integer programming. The material usage is used to represent the economic dimension and the carbon dioxide equivalent is used to represent the environmental dimension. The computed supported efficient solutions provide reasonable trade-off solutions for the considered bicycle manufacturing problem. (C) 2015 The Authors. Published by Elsevier B.V.

关键词： mixed integer programming multi-criteria decision making bi-criteria optimisation sustainable manufacturing

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Algorithms for Multi-Objective mixed integer programming Problems

Algorithms for Multi-Objective Mixed Integer Programming Pro...

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作者： Sierra Altamiranda, Alvaro Miguel University of South Florida

学位级别：Ph.D.

This thesis presents a total of 3 groups of contributions related to multi-objective optimization. The first group includes the development of a new algorithm and an open-source user-friendly package for optimization over the efficient set for bi-objective mixed integer linear programs. The second group includes an application of a special case of optimization over the efficient on conservation planning problems modeled with modern portfolio theory. Finally, the third group presents a machine learning framework to enhance criterion space search algorithms for multi-objective binary linear programming. In the first group of contributions, this thesis presents the first (criterion space search) algorithm for optimizing a linear function over the set of efficient solutions of bi-objective mixed integer linear programs. The proposed algorithm is developed based on the triangle splitting method (Boland et al.), which can find a full representation of the nondominated frontier of any bi-objective mixed integer linear program. The proposed algorithm is easy to understand and implement, and converges quickly to an optimal solution. An extensive computational study shows the efficacy of the algorithm. Is numerically shown in this thesis that the proposed algorithm can be used to quickly generate a provably high-quality approximate solution because it maintains a lower and an upper bound on the optimal value of the linear function at any point in time. Additionally, this thesis presents ***, a comprehensive julia package based on the proposed algorithm. The proposed package ex- tends the first implementation of the algorithm by adding two main features: (a) in addition to CPLEX, the package allows employing any single-objective solver supported by Math- ***, for example, GLPK, CPLEX, and SCIP; (b) the package supports execution on multiple processors and is compatible with the JuMP modeling language. An extensive computational study shows the efficacy of

关键词： Machine learning mixed integer programming Multi-objective optimization Nash bargaining solution Optimization over the efficient set Spatial conservation planning

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Scenario Based N-1 Transmission Expansion Planning using DC mixed integer programming

Scenario Based N-1 Transmission Expansion Planning using DC ...

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IEEE-Power-and-Energy-Society General Meeting (PESGM)

作者： Trpovski, Andrej Hamacher, Thomas TUMCREATE 1 CREATE Way10-02 CREATE Tower Singapore 138602 Singapore Tech Univ Munich Renewable & Sustainable Energy Syst D-85748 Garching Germany

ISBN: (纸本)9781728119816

This paper presents a scenario based mixed integer programming method to solve the transmission expansion planning problem with security constraints. To consider the N-1 line outages, the scenarios are introduced as a predefined set of parameters in the mathematical model. A DC power flow model is used as a simplified approach to represent the electrical system. The proposed expansion planning model is applied to the well known Garver 6 bus test system and a realistic 46 bus Brazilian test system. The versatility of the proposed method gives the freedom to test the expansion planning as a complete one-stage approach and as the common two-stage approach. The simulation results are presented to draw a conclusion of the performance of the proposed method.

关键词： Power System Planning Power Transmission mixed integer programming Optimization DC Power Flow Security Constraints

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A TWO LAYER mixed integer programming MODEL FOR DYNAMIC COMPOSITE WEBSERVICE SELECTION IN VIRTUAL ORGANIZATIONS INSPIRED BY LAYERING AS OPTIMIZATION DECOMPOSITION

A TWO LAYER MIXED INTEGER PROGRAMMING MODEL FOR DYNAMIC COMP...

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作者： ABIUD WAKHANU MULONGO University Of Nairobi

学位级别：博士

The key motivation for virtual organizations (VOs) is the need for business agility against a highly volatile and globally competitive market. The agility includes the ability to dynamically and efficiently package and deliver highly customized services that maximally satisfy the utility of service consumer demands over the Internet. Dynamic webservice composition (DWSC) is an essential Information Communication Technology (ICT) enabler of this form of agility in VOs. However, dynamic webservice composition remains a multiple criteria decision making (MCDM) nondeterministic polynomial (NP) hard optimization problem despite more than 10 years of extensive research. This makes the applicability of DWSC to problems of industrial relevance currently limited. mixed integer programming (MIP) is the most widely used technique in efficiently modelling the problem. There are two MIP models for the DWSC problem: a local planning strategy, herein L-MIP and a global planning strategy hereafter S-MIP. L-MIP is provably polynomial time and practically multiple times faster than S-MIP. However L-MIP lacks the ability to capture global inter workflow task webservice Quality of Service (QoS) constraints and generally is less optimal relative to S-MIP. It has been demonstrated that L-MIP generates composite webservices that are 20% to 30% worse in quality with respect to S-MIP. S-MIP on the other hand guarantees global optimality but is susceptible to exponential state space explosion, making the strategy limited to problems in which the number of service providers per business workflow task n is small. This thesis aimed to design a DWSC MIP global planning strategy that is more efficient than S- MIP. The second objective was to evaluate the performance of the proposed strategy versus S-MIP and L-MIP in terms of runtime efficiency and solution quality. The study proposed a two layer MIP model dubbed SLUM: Service Layered Utility Maximization. SLUM is inspired by the theory of Layerin

关键词： Dynamic Composite Webservice Selection mixed integer programming Layering Optimization Decomposition Virtual Organizations

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mixed integer programming Based Nested Partition Algorithm for Facility Location Optimization Problems

Mixed Integer Programming Based Nested Partition Algorithm f...

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2008 IEEE International Conference on Service Operations and Logistics, and Informatics(IEEE/SOLI’2008)(IEEE服务运作、物流与信息年会)

作者： Ming Xie Li Xia Jinyan Shao Yanjia Zhao Jin Dong IBM China Research LaboratoryZhongguancun Software ParkBeijing 100193 P.R.China Department of Automation Tsinghua UniversityBeijing 100084P.R.China IBM China Research Laboratory Zhongguancun Software Park Beijing 100193 P.R.China

Facility location optimization is very important for many retail industries,such as banking network,chain stores,and so *** covering location problem (MCLP) is one of the well-known models for these facility location optimization problems,which has earned extensive research ***,various practical requirements limit the application of the traditional formulation of MCLP,and the NP-hard characteristic makes effective approaches for large scale problems extremely *** paper focuses on a facility location problem motivated by a practical project of bank *** traditional MCLP formulation is generalized as a mixed integer programming (MIP) with considerations of various costs and revenues,multitype of facilities,and flexible coverage functions.A CPLEX-based hybrid nested partition algorithm is developed for large scale problems,and heuristic-based extensions are introduced to deal with extremely large *** formulation and algorithm are embedded into an asset called *** results demonstrate the effectiveness and efficiency of our approach.

关键词： mixed integer programming nested partition facility location optimization maximal covering location problem

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