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Combining revenue and equity in capacity allocation of imaging facilities

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2017年第2期256卷 619-628页

作者： Zhou, Liping Geng, Na Jiang, Zhibin Wang, Xiuxian Shanghai Jiao Tong Univ Sch Mech Engn Dept Ind Engn & Management 800 Dongchuan Rd Shanghai 200240 Peoples R China

Because of high procurement and operating costs, imaging facilities (e.g., magnetic resonance imaging (MRI)), are usually critical resources in hospitals. Hospital managers are under high pressure to pursue high utilization of the capacity, which leads to long waiting time for patients. However, different types of patients have different access time targets determined by their priorities according to the urgent levels and payments. The access time target is defined as the maximal amount of time between the appointment date and the examination date. For public hospitals, it is important to manage patient access to critical resources by considering the equity among different types of patients without sacrificing revenue. This paper proposes a nonlinear mixed-integer programming (NMIP) model for allocating the capacity of imaging facilities with the objective of maximizing revenue under the constraints of maintaining equity among different types of patients. The equity constraints are defined as the same access levels for different types of patients and the joint chance constraint for the same service levels in terms of waiting time. To solve this model, each time-slot, rather than the imaging facility, is considered as a server, which leads to an M/D/n queuing model. Based on an analysis of the M/D/n model, an approximation approach is proposed for the NMIP model, and CPLEX is used to solve the approximated model. Extensive numerical experiments based on real data from a large public hospital in Shanghai show the applicability and performance of the proposed model and investigate the impact of different parameters. (C) 2016 Elsevier B.V. All rights reserved.

关键词： OR in health services Capacity allocation Equity nonlinear mixed-integer programming Joint chance constraint

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SIMPLE nonlinear OPTIMIZATION-BASED SELECTION OF INSULATION MATERIAL AND WINDOW TYPE IN TURKEY:EFFECT OF HEATING AND COOLING BASE TEMPERATURES

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Journal of Green Building 2017年第2期12卷 79-94页

作者： Fehmi GörkemÜçtuğ Semra Ağralı School of Chemical Engineering and Analytical Science The University of ManchesterManchesterUKM139PL Department of Industrial Engineering MEF University34396SarıyerİstanbulTurkey

The energy-savings of four hypothetical households in different climatic regions of Turkey were calculated via a nonlinear mixed integer optimization *** ideal insulation material,its optimum thickness,and the ideal window type were *** standard degree days method was used with five different base temperatures for heating and five different base temperatures for *** climatic conditions of the region,the properties of the insulation options,the unit price of fuel and electricity and the base temperature are used as model inputs,whereas the combination of selected insulation material with its optimum thickness and window type are given as model *** Wool was found to be the ideal wall insulation material in all *** optimum window type was found to depend on the heating or cooling requirements of the house,as well as the lifetime of *** region where the energy saving actions are deemed most feasible has been identified as Erzurum(Region 4),followed by Antalya(Region 1).Finally,the effect of changing the base temperature on energy savings was investigated and the results showed that an approximate average increase of$15/℃ in annual savings is *** model can be used by any prospective home-owner who would like to maximize their energy savings.

关键词： Base temperature Degree days method HVAC systems Insulation thickness nonlinear mixed-integer programming Optimization

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Optimizing shipping-fee schedules to maximize e-tailer profits

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2013年第2期146卷 634-645页

作者： Jiang, Yuanchun Shang, Jennifer Liu, Yezheng Hefei Univ Technol Sch Management Hefei 230009 Anhui Peoples R China Univ Pittsburgh Joseph M Katz Grad Sch Business Pittsburgh PA 15260 USA Minist Educ Key Lab Proc Optimizat & Intelligent Decis Making Hefei 230009 Anhui Peoples R China

Shipping-fee charges by online retailers have been known to impact customers' order incidence and cart size. While the importance of managing shipping fees is well documented, few studies have provided normative guidelines for e-tailers to determine optimal shipping-fee schedules. This paper provides two nonlinear mixed-integer programming models to optimize e-tailers' shipping-fee charges for single and multiple product transactions. Given e-tailers' cost information and heterogeneity across consumers' reservation prices and delivery time requirements, our models aim to concurrently determine the optimal shipping-fee schedules and product selling prices. To solve the sophisticated models in real-time, we develop search techniques based on the concept of genetic algorithms. Numerical studies indicate that the proposed methods offer attractive product prices and low shipping charges. The proposed models not only meet the online requirement of instant response time, but also draw more customers and enhance e-tailer profitability. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Shipping-fee schedule nonlinear mixed-integer programming Genetic algorithm

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Single allocation hub location problem under congestion: Network owner and user perspectives

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EXPERT SYSTEMS WITH APPLICATIONS 2012年第3期39卷 3385-3391页

作者： de Camargo, R. S. Miranda, G. Univ Fed Minas Gerais Dept Ind Engn BR-31270901 Belo Horizonte MG Brazil

The single allocation hub location problem under congestion is addressed in this article. This mixed integer non-linear programming problem is referential in discrete location research having many real applications. Two different network design perspectives are proposed: the network owner and the network user. These perspectives can be translated into mathematical programming problems that are very hard to solve due to their inherently high combinatorial nature combined to the nonlinearities associated to congestion. A very efficient and effective generalized Benders decomposition algorithm is then deployed, enabling the solution of large scale instances in reasonable time. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Congestioned hub-and-spoke networks Generalized Benders decomposition nonlinear mixed-integer programming

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Supply chain optimisation with assembly line balancing

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2012年第11期50卷 3115-3136页

作者： Paksoy, Turan Ozceylan, Eren Gokcen, Hadi Selcuk Univ Dept Ind Engn TR-42031 Campus Konya Turkey Gazi Univ Dept Ind Engn TR-06570 Ankara Turkey

Supply chain management operates at three levels, strategic, tactical and operational. While the strategic approach generally pertains to the optimisation of network resources such as designing networks, location and determination of the number of facilities, etc., tactical decisions deal with the mid-term, including production levels at all plants, assembly policy, inventory levels and lot sizes, and operational decisions are related to how to make the tactical decisions happen in the short term, such as production planning and scheduling. This paper mainly discusses and explores how to realise the optimisation of strategic and tactical decisions together in the supply chain. Thus, a supply chain network (SCN) design problem is considered as a strategic decision and the assembly line balancing problem is handled as a tactical decision. The aim of this study is to optimise and design the SCN, including manufacturers, assemblers and customers, that minimises the transportation costs for determined periods while balancing the assembly lines in assemblers, which minimises the total fixed costs of stations, simultaneously. A nonlinear mixed-integer model is developed to minimise the total costs and the number of assembly stations while minimising the total fixed costs. For illustrative purposes, a numerical example is given, the results and the scenarios that are obtained under various conditions are discussed, and a sensitivity analysis is performed based on performance measures of the system, such as total cost, number of stations, cycle times and distribution amounts.

关键词： supply chain design assembly line balancing nonlinear mixed-integer programming

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Combining DC-programming and steepest-descent to solve the single-vehicle inventory routing problem

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COMPUTERS & INDUSTRIAL ENGINEERING 2011年第2期61卷 313-321页

作者： Zhong, Yiqing Aghezzaf, El-Houssaine Univ Ghent Dept Ind Management B-9052 Zwijnaarde Belgium

The single-vehicle cyclic inventory routing problem (SV-CIRP) is concerned with a repeated distribution of a product from a single depot to a selected subset of retailers having stable demands. If a retailer is selected for replenishment, the supplier collects a retailer-related fixed reward. The objective is to determine the subset of retailers to cyclically replenish, the quantities to be delivered to each, and to design the vehicle delivery routes so that the expected total distribution and inventory cost is minimized while the total collected rewards from the selected retailers is maximized. The resulting distribution plan must prevent stockouts from occurring at each retailer. In this paper, the underlying optimization problem for the SV-CIRP is formulated as a mixed-integer program with linear constraints and a nonlinear objective function. An optimization approach combining DC-programming and Branch-and-Bound within a steepest descent hybrid algorithm, denoted by DCA-SDHA, is developed for its solution. The approach is tested on some randomly generated problems and the obtained results are compared with results from the standard steepest descent hybrid algorithm (SDHA). These encouraging results show that the proposed approach is indeed computationally more effective and is worth being further investigated for the solution of medium to large instances. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Inventory-routing nonlinear mixed-integer programming DC-programming Global optimization

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Lifting inequalities: a framework for generating strong cuts for nonlinear programs

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MATHEMATICAL programming 2010年第1期121卷 61-104页

作者： Richard, Jean-Philippe P. Tawarmalani, Mohit Purdue Univ Krannert Sch Management W Lafayette IN 47907 USA Purdue Univ Sch Ind Engn W Lafayette IN 47907 USA

In this paper, we introduce the first generic lifting techniques for deriving strong globally valid cuts for nonlinear programs. The theory is geometric and provides insights into lifting-based cut generation procedures, yielding short proofs of earlier results in mixed-integer programming. Using convex extensions, we obtain conditions that allow for sequence-independent lifting in nonlinear settings, paving a way for efficient cut-generation procedures for nonlinear programs. This sequence-independent lifting framework also subsumes the superadditive lifting theory that has been used to generate many general-purpose, strong cuts for integer programs. We specialize our lifting results to derive facet-defining inequalities for mixed-integer bilinear knapsack sets. Finally, we demonstrate the strength of nonlinear lifting by showing that these inequalities cannot be obtained using a single round of traditional integer programming cut-generation techniques applied on a tight reformulation of the problem.

关键词： nonlinear mixed-integer programming Cutting planes Bilinear knapsacks Convex extensions Sequence-independent lifting Elementary closures

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A Combined DC programming and Branch-and-Bound to Solve the Single-Vehicle Cyclic Inventory Routing Problem with a Fixed Cycle Time

A Combined DC Programming and Branch-and-Bound to Solve the ...

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International Conference on Computers and Industrial Engineering (CIE39)

作者： Zhong, Yiqing Aghezzaf, El-Houssaine Univ Ghent Dept Ind Management B-9052 Ghent Belgium

ISBN: (纸本)9781424441358

The single-vehicle cyclic inventory routing problem (SV-CIRP) consists of distributing a given product, on a cyclical basis, from a single depot to a selected subset of retailers. A fixed retailer-related reward is collected if a retailer is selected for the cyclic replenishment. The objective is thus to select a subset of retailers to be replenished and to develop an optimal cyclic distribution plan that minimizes expected distribution and inventory costs and in the same time maximizes the sum of rewards collected from the selected retailers. This distribution plan must prevent stockout from occurring at any of the selected retailers during each cycle. The underlying optimization problem for this SV-CIRP can be formulated as a mixed-integer program with linear constraints and a nonlinear objective function. In this paper, a DC-programming approach combined with Branch-and-Bound is used to solve the SV-CIRP with a fixed cycle time. The approach is then tested on some cases given in the literature, and the obtained results are compared with the results from the usual Branch-and-Bound. These preliminary results show that DC-programming combined with Branch-and-Bound is more effective that the usual Branch-and-Bound based LP-relaxations. The approach is therefore worth being investigated further for the solution of the cyclic inventory routing problem (CIRP).

关键词： Inventory Transportation nonlinear mixed-integer programming DC-programming

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Finding optimal nuclear reactor core reload patterns using nonlinear optimization and search heuristics

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ENGINEERING OPTIMIZATION 1999年第2期32卷 143-176页

作者： Quist, AJ Van Geemert, R Hoogenboom, JE Illés, T De Klerk, E Roos, C Terlaky, T Delft Univ Technol Fac Informat Technol & Syst Delft Netherlands Delft Univ Technol Interfac Reactor Inst Delft Netherlands Eotvos Lorand Univ Dept Operat Res Budapest Hungary

A simplified but still quite realistic model of the nuclear reactor fuel management problem is used to search for optimal fuel loading schemes. Several adaptations and model adjustments are described that make the model tractable for a general nonlinear mixed-integer solver. Results are compared with results from pairwise interchange optimization. Use of solutions from nonlinear mixed-integer optimization as starting values for local search heuristics leads to powerful optimization methods.

关键词： nonlinear mixed-integer programming nonlinear assignment fuel management nuclear reactors

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