scholarly journals Mathematical Programming Approach to the Optimality of the Solution for Deterministic Inventory Models with Partial Backordering

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Irena Stojkovska
Keyword(s):  
Mathematical Programming ◽  
Programming Problem ◽  
Optimal Decision ◽  
Alternative Proof ◽  
Programming Approach ◽  
Mathematical Programming Problem ◽  
Inventory Models ◽  
Partial Backordering ◽  
Mathematical Programming Approach

We give an alternative proof of the optimality of the solution for the deterministic EPQ with partial backordering (EPQ-PBO) [Omega, vol. 37, no. 3, pp. 624–636, 2009]. Our proof is based on the mathematical programming theory. We also demonstrate the determination of the optimal decision policy through solving the corresponding mathematical programming problem. We indicate that the same approach can be used within other inventory models with partial backordering, and we consider additional models.

scholarly journals Formulating Intuitionistic Fuzzy Regression Models: A Mathematical Programming Approach

2021 ◽  
Author(s):  
Sheng-Hsing Nien ◽  
Liang-Hsuan Chen
Keyword(s):  
Mathematical Programming ◽  
Regression Models ◽  
Fuzzy Regression ◽  
Distance Measures ◽  
Programming Approach ◽  
Mathematical Programming Problem ◽  
Explanatory Variables ◽  
Intuitionistic Fuzzy ◽  
Mathematical Programming Approach ◽  
Ordinary Regression

Abstract This study develops a mathematical programming approach to establish intuitionistic fuzzy regression models (IFRMs) by considering the randomness and fuzziness of intuitionistic fuzzy observations. In contrast to existing approaches, the IFRMs are established in terms of five ordinary regression models representing the components of the estimated triangular intuitionistic fuzzy response variable. The optimal parameters of the five ordinary regression models are determined by solving the proposed mathematical programming problem, which is linearized to make the resolution process efficient. Based on the concepts of randomness and fuzziness in the formulation processes, the proposed approach can improve on existing approaches’ weaknesses with establishing IFRMs, such as the limitation of symmetrical triangular membership (or non-membership) functions, the determination of parameter signs in the model, and the wide spread of the estimated responses. In addition, some numerical explanatory variables included in the intuitionistic fuzzy observations are also allowed in the proposed approach, even though it was developed for intuitionistic fuzzy observations. In contrast to existing approaches, the proposed approach is general and flexible in applications. Comparisons show that the proposed approach outperforms existing approaches in terms of similarity and distance measures.

Large Displacement Elastoplastic Analysis of Space Trusses as a Mathematical Programming Problem

1998 ◽  
Vol 13 (3) ◽  
pp. 127-136 ◽  
Author(s):  
S.H. Xia ◽  
F. Tin-Loi
Keyword(s):  
Mathematical Programming ◽  
Programming Problem ◽  
Nonlinear Complementarity Problem ◽  
Geometrical Nonlinearity ◽  
Small Strain ◽  
Large Displacement ◽  
Elastoplastic Analysis ◽  
Programming Approach ◽  
Mathematical Programming Problem ◽  
Space Trusses

A mathematical programming approach is proposed for the large displacement elastoplastic analysis of space trusses. Features of the general methodology include the preservation of static-kinematic duality through the concept of fictitious forces and deformations, exact descriptions of equilibrium and compatibility for arbitrarily large displacements, albeit small strain, that can be specialized to any order of geometrical nonlinearity, and a complementarity description of the elastoplastic constitutive laws. The finite incremental formulation developed takes the form of a special mathematical programming problem known as a nonlinear complementarity problem for which a predictor-corrector type numerical scheme is proposed.

scholarly journals Modelling and Allocation of Crops: Mathematical Programming Approach

2019 ◽  
pp. 1-5
Author(s):  
M. A. Lone ◽  
S. A. Mir ◽  
Tabasum Mushtaq
Keyword(s):  
Mathematical Programming ◽  
Programming Problem ◽  
Fuzzy Programming ◽  
Programming Approach ◽  
Cropping Pattern ◽  
Vegetable Crops ◽  
Mathematical Programming Approach ◽  
Programming Techniques ◽  
Total Profit ◽  
Optimal Cropping

Mathematical programming techniques are commonly used by decision makers for achieving efficiency in agricultural production planning. Due to increasing demands of growing population of world, one needs to utilize the limited available resources in the most efficient and economic way. In this paper, the fractional programming problem is formulated and is used to determine the optimal cropping pattern of vegetable crops in such a way that the total profit is maximized. The solution of the formulated Fuzzy programming problem is obtained using LINGO.

scholarly journals Le coût de l’électricité au Québec : 1976-1990

2009 ◽  
Vol 54 (4) ◽  
pp. 431-462
Author(s):  
Marcel Boyer ◽  
Fernand Martin
Keyword(s):  
Mathematical Programming ◽  
Marginal Cost ◽  
Operating Cost ◽  
Programming Approach ◽  
Cost Of Electricity ◽  
Investment Plan ◽  
Mathematical Programming Approach

In this paper, the authors develop a model for evaluating the marginal cost of electricity in the Province of Quebec for the period 1976-90. This model requires only available data, namely, the operating cost for the year 1976-77 and the investment plan for the 1976-1985 period. It makes possible the determination of the marginal cost of electricity without having to use a mathematical programming approach for which the required data are not always available.

scholarly journals An Approach of Trustworthy Measurement Allocation Based on Sub-Attributes of Software

Mathematics ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 237 ◽  
Author(s):  
Hongwei Tao ◽  
Hengyang Wu ◽  
Yixiang Chen
Keyword(s):  
Mathematical Programming ◽  
Software Quality ◽  
Necessary Conditions ◽  
Optimal Solution ◽  
Research Field ◽  
Programming Approach ◽  
Mathematical Programming Problem ◽  
Important Research ◽  
Mathematical Programming Approach ◽  
Software Trustworthiness

Measurement of software trustworthiness is an important research field in the software engineering, which is very useful for analyzing the software quality. In this paper, we propose a mathematical programming approach to allocate the trustworthy degree to each sub-attribute of some software attribute appropriately and then to make the trustworthy degree of this attribute maximize under some constraint conditions. Some sufficient or necessary conditions for analyzing this mathematical programming problem are investigated. Moreover, a polynomial allocation algorithm is given for computing the optimal solution of this mathematical programming. Finally, an example is given in order to show the significance of this work. The results obtained here are useful for improving the software quality by adjusting the trustworthy degree of each sub-attribute under the same cost.

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