mathematical programming (MP) models are among the most widely used tools in operations research and management science. In this dissertation, we use MP approaches, mainly relying on mixed-integer programming (MIP) mo...
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mathematical programming (MP) models are among the most widely used tools in operations research and management science. In this dissertation, we use MP approaches, mainly relying on mixed-integer programming (MIP) modeling, to solve logistics problems in the following two areas: home healthcare (HHC) and truckload transportation procurement. HHC is health or supportive care provided in the patient’s home by healthcare professionals. Approximately 12 million individuals currently receive HHC services from more than 33,000 providers with over 1 million staff members. However, 65% of home care and hospice agencies are facing nurse staff vacancies and 84% of nurse staff worked overtime during last week at the interview time. To help improve efficiency of the HHC workforce and improve patient outcomes, we develop an operational dispatching (routing) model that assigns care workers to patients anddetermines the optimal visiting sequences and start times. An appointment scheduling decision support system is developed to handle the clients’ appointment requests dynamically. The model allows the use of time windows and time-dependent travel speeds. We develop and compare heuristic approaches for solving this problem and conduct numerical experiments on different sized instances. According to the results, a hybrid algorithm based on genetic algorithm and particle swarm optimization is further proposed. In freight transportation service procurement, shippers sell service contracts to carriers based on negotiated transportation rates and service level by utilizing a competitive auction process. Recently, several large shippers and third-party-logistics (3PL) providers have turned to combinatorial auction mechanisms to reduce their transportation costs, where the bidding carriers can quote prices on packages in combination of individual lanes. We address the problem of truckload transportationprocurement via combinatorial auctions from two perspectives. i) a carrier perspective
A method of unit commitment in an electric utility system is discussed. The need for production costing as a part of optimum unit commitment is emphasized. A lambda separable programming technique is presented which a...
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A method of unit commitment in an electric utility system is discussed. The need for production costing as a part of optimum unit commitment is emphasized. A lambda separable programming technique is presented which allows the use of separation variables, lambda , to represent the fixed charge component as well as the nonlinear component of the objective function. The method is tested using a hypothetical system of generating units including nuclear, fossil, hydro, thermal peaking and pumped storage. The daily unit commitment schedule for these generators is found using the optimization technique presented. Also, the suitability of this type of algorithm to study the inter-fuel substitutability is discussed.
Two mathematical programming procedures for treating nonlinear problems involving mixed variables are presented. One involves a relatively simple concept. First an optimum is located treating all variables as continuo...
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Two mathematical programming procedures for treating nonlinear problems involving mixed variables are presented. One involves a relatively simple concept. First an optimum is located treating all variables as continuous. Adjacent discrete points are then evaluated in order of increasing distance from the all-continuous optimum, each evaluation requiring an optimization of the continuous variables, if any, until a satisfactory design is found. The other method utilizes an optimal discrete search to locate the optimum. These procedures are applied to the minimum weight design of stiffened, cylindrical shells where they prove to be effective.
In this article, a novel approach is presented for the simulation of failure processes of structures in extreme events such as earthquakes. Models of material behavior are represented using a Generalized Standard Mate...
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In this article, a novel approach is presented for the simulation of failure processes of structures in extreme events such as earthquakes. Models of material behavior are represented using a Generalized Standard Material framework, and the governing equations are formulated using a Mixed Lagrangian Formalism. This results in the failure simulation computations being cast as different types of mathematical programs. Efficient strategies are devised to solve these mathematical programs in the context of large-scale problems of practical interest. Numerical examples are presented to illustrate the approach.
The place of mathematical programming methods in structural optimization is now well established after some 15 years of research and development. Numerous design applications have been reported for aircraft and ship c...
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The place of mathematical programming methods in structural optimization is now well established after some 15 years of research and development. Numerous design applications have been reported for aircraft and ship components, steel and concrete buildings and bridges and other civil and mechanical systems. This paper reviews these developments and attempts to establish a general framework for the type of design problems that can be formulated and solved. Design problems are divided into three categories for application including element design, system design and discrete decisions. The techniques described include unconstrainted minimization, linear programming based methods and dynamic programming. A discussion is presented of the interrelationships of the mathematical programming approach to optimization with both the theoretical optimality criteria and the direct design or structural index method.
An integer mathematical program that is useful in the context of manufacturing system design and evaluation is presented. In particular, the design of adaptable/programmable assembly systems is considered, although th...
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An integer mathematical program that is useful in the context of manufacturing system design and evaluation is presented. In particular, the design of adaptable/programmable assembly systems is considered, although the method presented is equally applicable to flexible manufacturing systems. The system design decision entails the selection of assembly stations to include in the system, plus the assignment of assembly tasks to these stations.
Efficient research method represents the primary content of hydrogen networks optimization. In the view of methodology, as pinch analysis is not specialized in precisely matching a network and mathematical programming...
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We give a short review of existing mathematical programming based bounds for kissing numbers. The kissing number in K dimensions is the maximum number of unit balls arranged around a central unit ball in such a way th...
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This paper presents two solution techniques for constructing a minimal weighted tree connecting a fixed set of n terminal vertices while allowing extra vertices to be added to the tree to reduce the cost or length of ...
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ISBN:
(纸本)9780897916585
This paper presents two solution techniques for constructing a minimal weighted tree connecting a fixed set of n terminal vertices while allowing extra vertices to be added to the tree to reduce the cost or length of the connection. The problem discussed is a variation of the Steiner tree problem that reduces to the classical Steiner tree problem for many special cases. It is also a generalization of the planar Steiner tree problem. The algorithms seek to determine the location of points (Steiner points) such that each terminal vertex is connected to a Steiner point. The Steiner points are then connected to each other and the algorithm minimizes total cost. We present a solution to this problem for a modest number of terminal vertices using a mathematical programming approach and combinatorics. This approach is guaranteed to find the optimal points (Steiner points) that minimize the total cost. We also construct an algorithm that iteratively combines the early use of mathematical programming along with a hybrid genetic algorithm. The solution techniques were tested extensively on small planar problems but were also applied to large problems in two-, three- and five-dimensional space. The genetic algorithm is used to determine the appropriate structure of a solution and the mathematical programming algorithm determines the optimal location of Steiner points for each structure. The structure determines the assignment of terminal vertices to the Steiner points. The mathematical programming algorithm is the optimization part of a very powerful evaluation function for the genetic algorithm approach to the problem.
A math programming model is formulated for selecting assembly stations and assigning operations to these stations so as to satisfy a production volume requirement at minimum system cost. A branch-and-bound algorithm, ...
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A math programming model is formulated for selecting assembly stations and assigning operations to these stations so as to satisfy a production volume requirement at minimum system cost. A branch-and-bound algorithm, coupled wiht a subgradient optimization procedure, is proposed. The model and algorithm are demonstrated by example on a system design problem for assembling automobile alternators. The model is applicable to many kinds of manufacturing systems.
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