This paper addresses a routing problem where the fulfillment of transport requests requires two types of transport resources, namely, passive and active means of transport. The passive means are used for holding the c...
详细信息
This paper addresses a routing problem where the fulfillment of transport requests requires two types of transport resources, namely, passive and active means of transport. The passive means are used for holding the cargo that is to be shipped from pickup to delivery locations. The active means take up the passive means and carry them from one location to another. Compared to classical vehicle routing problems, the additional challenge in this combined routing problem is that the operations of both transport resources have to be synchronized. In this paper, we provide a modeling approach for the joint routing of passive and active means of transport. We solve the problem by large neighborhood search meta-heuristics that utilize various problem-specific components, for example local search techniques for the routes of active and passive means. A computational study on a large set of benchmark instances is used for assessing the performance of the meta-heuristics.
In this paper we consider the problem of selecting an absolute return portfolio. This is a portfolio of assets that is designed to deliver a good return irrespective of how the underlying market (typically as represen...
详细信息
In this paper we consider the problem of selecting an absolute return portfolio. This is a portfolio of assets that is designed to deliver a good return irrespective of how the underlying market (typically as represented by a market index) performs. We present a three-stage mixed-integer zero-one program for the problem that explicitly considers transaction costs associated with trading. The first two stages relate to a regression of portfolio return against time, whilst the third stage relates to minimising transaction cost. We extend our approach to the problem of designing portfolios with differing characteristics. In particular we present models for enhanced indexation (relative return) portfolios and for portfolios that are a mix of absolute and relative return. Computational results are given for portfolios derived from universes defined by S&P international equity indices. (C) 2013 Elsevier Ltd. All rights reserved.
During a medical emergency in the USA, critical medical supplies such as medications, vaccines, gloves, masks and ventilators, are delivered to one location within each state. The state and local governments are respo...
详细信息
During a medical emergency in the USA, critical medical supplies such as medications, vaccines, gloves, masks and ventilators, are delivered to one location within each state. The state and local governments are responsible for delivering the supplies from this location, called the receiving, staging and storage (RSS) site to the points of dispense (PODs). The supplies can be sent from the RSS to PODs directly or via regional distribution nodes (RDNs). We develop two mixed-integer programming models for this emergency logistics network (ELN) problem. These two models are simplified to obtain equivalent models that lead to the same results, but with fewer constraints. The equivalent models are much less complex and have lower computational memory and time requirements. We optimise the required number and locations of RSSs and RDNs needed to satisfy the demands at the PODs within the required time windows. Experiments are conducted to illustrate how the proposed models can be applied to a real life problem.
We propose an approximate solution strategy for multi-parametric mixedinteger linear programming (mp-MILP) problems with parameter dependency at multiple locations in the model. A two-stage solution strategy, consist...
详细信息
We propose an approximate solution strategy for multi-parametric mixedinteger linear programming (mp-MILP) problems with parameter dependency at multiple locations in the model. A two-stage solution strategy, consisting of an approximation stage and a multi-parametric programming stage, is introduced. At the approximation stage, surrogate mp-MILP models are derived by overestimating bilinear terms in the constraints over an ab initio partitioning of the domain. We then incorporate piecewise affine relaxation based models using a linear partitioning scheme and a logarithmic partitioning scheme, respectively. The models are tuned by the number of partitions chosen. Problem sizes of the varied models, and computational requirements for the algorithmic procedure are compared. The conservatism of the suboptimal solution of the mp-MILP problem for the piecewise affine relaxation based two-stage method is discussed. (C) 2013 Elsevier Ltd. All rights reserved.
Evacuation is an important disaster management tool. Evacuating a large region by automobile (the most commonly used mode) is a difficult task, especially as high levels of traffic congestion often form. This paper st...
详细信息
Evacuation is an important disaster management tool. Evacuating a large region by automobile (the most commonly used mode) is a difficult task, especially as high levels of traffic congestion often form. This paper studies the use of demand-based strategies, specifically, the staging and routing of evacuees. These strategies attempt to manage demand in order to reduce or eliminate congestion. A strategic mixed-integer programming planning model that accounts for evacuation dynamics and congestion is used to study these strategies. The strategies adopted incorporate different evacuee types based on destination requirements and shelter capacity restrictions. The main objective studied is to minimize the network clearance time. We examine the structure of optimal strategies, yielding insights into the use of staging and routing in evacuation management. These insights are then used to develop effective solution procedures. To demonstrate the efficacy of the proposed solution technique, we provide computational experience using a large realistic example based on Virginia Beach.
A two-class classification problem is considered where the objects to be classified are bags of instances in d-space. The classification rule is defined in terms of an open d-ball. A bag is labeled positive if it meet...
详细信息
A two-class classification problem is considered where the objects to be classified are bags of instances in d-space. The classification rule is defined in terms of an open d-ball. A bag is labeled positive if it meets the ball and labeled negative otherwise. Determining the center and radius of the ball is modeled as a SVM-like margin optimization problem. Necessary optimality conditions are derived leading to a polynomial algorithm in fixed dimension. A VNS type heuristic is developed and experimentally tested. The methodology is extended to classification by several balls and to more than two classes. (C) 2013 Elsevier Ltd. All rights reserved.
Hospitals typically lack effective enterprise level strategic planning of bed and care resources, contributing to bed census levels that are statistically "out of control." This system dysfunction manifests ...
详细信息
Hospitals typically lack effective enterprise level strategic planning of bed and care resources, contributing to bed census levels that are statistically "out of control." This system dysfunction manifests itself in bed block, surgical cancelation, ambulance diversions, and operational chaos. This is the classic hospital admission scheduling and control (HASC) problem, which has been addressed in its entirety only through inexact simulation-based search heuristics. This paper develops new analytical models of controlled hospital census that can, for the first time, be incorporated into a mixed-integer programming model to optimally solve the strategic planning/scheduling portion of the HASC. Our new solution method coordinates elective admissions with other hospital subsystems to reduce system congestion. We formulate a new Poisson-arrival-location model (PALM) based on an innovative stochastic location process that we developed and call the patient temporal resource needs model. We further extend the PALM approach to the class of deterministic controlled-arrival-location models (d-CALM) and develop linearizing approximations to stochastic blocking metrics. This work provides the theoretical foundations for an efficient scheduled admissions planning system as well as a practical decision support methodology to stabilize hospital census.
This paper presents an optimization model for the design of global supply chains where the emphasis is made on transfer pricing for both tangible and intangible elements. We adopt the profit split transfer pricing met...
详细信息
This paper presents an optimization model for the design of global supply chains where the emphasis is made on transfer pricing for both tangible and intangible elements. We adopt the profit split transfer pricing method which is dictated by OECD guidelines and may be accepted by fiscal authorities. The proposed model is particularly suited for the offshoring context. In addition to transfer pricing, the model integrates several relevant decisions such as the location of tangible and intangible activities. Intangible activities refer to R&D and supplier management. Experimental analyses are conducted in order to prove the feasibility and the solvability of the model and to show the impacts of transfer pricing on supply chain decisions and profits. (C) 2014 Elsevier Ltd. All rights reserved.
One of the essential components of a branch-and-bound based mixedinteger linear programming (MIP) solver is the branching rule. Strong branching is a method used by many state-of-the-art branching rules to select the ...
详细信息
One of the essential components of a branch-and-bound based mixedinteger linear programming (MIP) solver is the branching rule. Strong branching is a method used by many state-of-the-art branching rules to select the variable to branch on. It precomputes the dual bounds of potential child nodes by solving auxiliary linear programs and thereby helps to take good branching decisions that lead to a small search tree. In this paper, we describe how these dual bound predictions can be improved by including domain propagation into strong branching. Domain propagation is a technique that MIP solvers usually apply at every node of the branch-and-bound tree to tighten the local domains of variables. Computational experiments on standard MIP instances indicate that our improved strong branching method significantly improves the quality of the predictions and causes almost no additional effort. For a full strong branching rule, we are able to obtain substantial reductions of the branch-and-bound tree size as well as the solving time. Moreover, the state-of-the-art hybrid branching rule can be improved this way as well.
In order to derive continuity and stability of two-stage stochastic programs with mixed-integer recourse when all coefficients in the second-stage problem are random, we first investigate the quantitative continuity o...
详细信息
In order to derive continuity and stability of two-stage stochastic programs with mixed-integer recourse when all coefficients in the second-stage problem are random, we first investigate the quantitative continuity of the objective function of the corresponding continuous recourse problem with random recourse matrices. Then by extending derived results to the mixed-integer recourse case, the perturbation estimate and the piece-wise lower semi-continuity of the objective function are proved. Under the framework of weak convergence for probability measure, the epi-continuity and joint continuity of the objective function are established. All these results help us to prove a qualitative stability result. The obtained results extend current results to the mixed-integer recourse with random recourse matrices which have finitely many atoms.
暂无评论