This thesis builds an optimization decision model that can be used to determine the optimum ratio of the two vehicles that the Army and Marine Corps can purchase to minimize costs while taking into account constraints...
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This thesis builds an optimization decision model that can be used to determine the optimum ratio of the two vehicles that the Army and Marine Corps can purchase to minimize costs while taking into account constraints related to each vehicles' capabilities, such as required off-road capabilities and transport ease for missions supported by the services. The proposed optimization decision model is a cost minimizing non-linear programming model that also accounts for changes in the average production cost of each type of vehicle by embedding a cumulative average cost formula into the objective function of the model.
Demand and supply pattern for most products varies during their life cycle in the markets. In this paper, the author presents a transportation problem with non-linear constraints in which supply and demand are symmetr...
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Demand and supply pattern for most products varies during their life cycle in the markets. In this paper, the author presents a transportation problem with non-linear constraints in which supply and demand are symmetric trapezoidal fuzzy value. In order to reflect a more realistic pattern, the unit of transportation cost is assumed to be stochastic. Then, the non-linear constraints are linearized by adding auxiliary constraints. Finally, the optimal solution of the problem is found by solving the linearprogramming problem with fuzzy and crisp constraints and by applying fuzzy programming technique. A new method proposed to solve this problem, and is illustrated through numerical examples. Multi-objective goal programming methodology is applied to solve this problem. The results of this research were developed and used as one of the Decision Support System models in the Logistics Department of Kayson Co.
In this paper, a new method is presented for the optimisation of force distribution for combined traction/braking and cornering. In order to provide a general, simple and flexible problem formulation, the optimisation...
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In this paper, a new method is presented for the optimisation of force distribution for combined traction/braking and cornering. In order to provide a general, simple and flexible problem formulation, the optimisation is addressed as a quadratically constrained linearprogramming (QCLP) problem. Apart from fast numerical solutions, different driveline configurations can be included in the QCLP problem in a very straightforward fashion. The optimisation of the distribution of the individual wheel forces using the quasi-steady-state assumption is known to be useful for the study of the influence of particular driveline configurations on the combined lateral and longitudinal grip envelope of a particular vehicle-driveline configuration. The addition of the QCLP problem formulation makes another powerful tool available to the vehicle dynamics analyst to perform such studies.
Regularity conditions or constraint qualifications play an important role in mathematical programming. In this article we present a relaxed version of the constant rank constraint qualification (CRCQ) which is weaker ...
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Regularity conditions or constraint qualifications play an important role in mathematical programming. In this article we present a relaxed version of the constant rank constraint qualification (CRCQ) which is weaker than the original CRCQ for mixed-constrained non-linear programming problems and is still a regularity condition. The main aim of this article is to show that the relaxed CRCQ (and, consequently, CRCQ too) implies the R-regularity (in other terms the error bound property) of a system of inequalities and equalities. In the same way we prove that the constant positive linear dependence (CPLD) condition also implies R-regularity.
In this paper open loop optimal trajectories for downhill driving are described. Problem formulation including process modelling, model simplification, transformation into a finite optimisation problem, and implementa...
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In this paper open loop optimal trajectories for downhill driving are described. Problem formulation including process modelling, model simplification, transformation into a finite optimisation problem, and implementation into the TOMLAB optimisation package are presented. Results show that there is a large potential in controlling the complete brake system of a heavy duty truck and thereby simultaneously improve both mean speed (transport efficiency) and component wear cost. The resulting optimal trajectories define the upper limit for what is theoretically achievable in a real, closed loop, controller implementation and can be used to both inspire and verify the development of such algorithms.
In the paper, one focuses on the problem of duality in non-linear programming, applied to the solution of no-tension problems by means of Limit Analysis (LA) theorems for Not Resisting Tension (NRT) models. In details...
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In the paper, one focuses on the problem of duality in non-linear programming, applied to the solution of no-tension problems by means of Limit Analysis (LA) theorems for Not Resisting Tension (NRT) models. In details, one demonstrates that, starting from the application of the duality theory to the non-linear program defined by the static theorem approach for a discrete NRT model, this procedure results in the definition of a dual problem that has a significant physical meaning: the formulation of the kinematic theorem.
Probabilistic programming is used in some optimization problems where some or all parameters are considered as random variables, in order to deal with uncertainty, which is an inherent feature of the system. The situa...
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Probabilistic programming is used in some optimization problems where some or all parameters are considered as random variables, in order to deal with uncertainty, which is an inherent feature of the system. The situation of multiple parameters may exist in a decision making problem in our real life. The multi-choice programming can not only avoid the underestimation of parameters, but also can decide the appropriate parameter from multiple parameters. This paper deals with a probabilistic linearprogramming problem, where the right hand side parameters of probabilistic constraints are multichoice in nature and rest of the parameters are independent random variables. In this paper the probabilistic programming problem is converted to an equivalent deterministic mathematical programming model. The resulting model is then solved by standard linear or non-linear programming techniques. A numerical example is presented to illustrate the methodology.
Product service system (PSS) planning has been attracting attentions of global manufacturers to change from providing only products to offering both products and their services as a whole. The PSS planning approach ca...
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Product service system (PSS) planning has been attracting attentions of global manufacturers to change from providing only products to offering both products and their services as a whole. The PSS planning approach can maintain the functionality of products for customers throughout the whole product life-cycle. Identification of the product and service parameters in early design stages plays a critical role in PSS development. The PSS planning is usually started by the mapping from customer requirements (CRs) in the customer domain to engineering characteristics (ECs), including product-related ECs (P-ECs) and service-related ECs (S-ECs), in the functional domain. In this paper, a systematic decision-making approach for PSS planning is developed to determine the optimal fulfillment levels of ECs considering requirements of customers and manufacturers. The PSS planning is conducted through four phases. First, the initial weights of ECs considering customer needs are achieved based on fuzzy pairwise comparison. Second. the data envelopment analysis (DEA) approach is applied to obtain the final weights of ECs considering customer requirements as well as other requirements of the manufacturers. Third, the ECs are categorized into different Kano attribute classes using fuzzy Kano's questionnaire (FKQ) and fuzzy Kano's mode (FKM) for evaluation of the PSS. In the last phase, non-linear programming is carried out to maximize the fulfillment levels of ECs. A case study is carried out to demonstrate the effectiveness of the developed optimal PSS planning approach. (C) 2011 Elsevier Ltd. All rights reserved.
In this paper a non-linear programming model is developed for a typical factory which presents the optimal values and times for the electrical energy consumption based on doing activities and operations in factory. Mo...
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In this paper a non-linear programming model is developed for a typical factory which presents the optimal values and times for the electrical energy consumption based on doing activities and operations in factory. Model's appropriate parameters are been with due attention to define tariffs and limitations by distributions of electrical energy. Furthermore, the operational constraints of the typical factory are formulated and these constraints are merged with the constraints of appropriate consumption. (C) 2006 Elsevier Inc. All rights reserved.
The paper describes the essential differences in determining optimal gradation of hot mix asphalt (HMA) mixture used in road building at the stages of its selection, initial design and production, and presents the res...
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The paper describes the essential differences in determining optimal gradation of hot mix asphalt (HMA) mixture used in road building at the stages of its selection, initial design and production, and presents the respective algorithms. The models of constrained and unconstrained non-linear optimization are developed, allowing us to choose the best HMA mixture gradation based on mineral materials, whose gradation is known, when the total percent passing of HMA mixture aggregates is considered to be equally important for all sieves, or when preference is given to some of the sieves. A new linear optimization problem best suited for practical use due to its simplicity is offered. By introducing weight coefficients for the dimensions of the objective function of the model, zero deviations of the percent passing of HMA mixture aggregates from their standard values may be easily obtained, based on the preferences set. All mineral materials (aggregates) obtained at batch-type asphalt mixing plants should be used for HMA production. Their total mass is equal to unity, while the mass of each material is a positive quantity, and a predetermined relationship between the masses of imported filler and the reclaimed dust is used. In the experimental part of the work, the problems were solved using the SAS system. (C) 2010 Elsevier Ltd. All rights reserved.
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