scholarly journals Binary goal programming model for optimizing tire selection using branch and bound algorithm

Author(s):  
Shady Aly

The problem of assessment and adoption of automotive tyre design specifications has not been addressed sufficiently in literature. This is in spite of its significance as a crucial component relevant to design and safety of the automobile. In this paper, a multi-objective optimization model of the tyre design trademark adoption decision is proposed. Multi-attribute or multi-criterion decision making techniques are heuristics providing good solution, but do not guarantee optimum solution. Up to date, there is no optimal yielding method for selection of vehicle tyre manufacturer or trademark based on prespecified design targets. The proposed model is formulated as a binary goal programming model for optimizing tyre trademark design selection decision by adopting an optimal tyre design trademark that best achieve design targets. The model is solved by the branch and bound algorithm. One advantage of the proposed model is flexibility to incorporate multiple design targets, tolerance limits and different constraints. The proposed model can support efficient and effective decision making concerning the adoption of tyre trademark design for new automobile or to re-adopt new design for new road vehicle operating conditions.

1979 ◽  
Vol 3 (4) ◽  
pp. 31-41 ◽  
Author(s):  
Sang M. Lee ◽  
Robert T. Justis ◽  
Lori Sharp Franz

There are few analytical and managerial tools available to assist the small business decision maker. This paper presents a practical goal Programming model which can be easily generalized to fit the planning needs of most small businesses. Specifically the model explicitly considers the multiple goals and priorities of the owner-manager and determines if these goals can be accomplished under various demand Projections. An illustrative example of the use of this model with a small fast-food business is given.


2016 ◽  
Vol 3 (6) ◽  
pp. 1447-1459 ◽  
Author(s):  
Serkan Erbis ◽  
Sagar Kamarthi ◽  
Amir Abdollahi Namin ◽  
Ali Hakimian ◽  
Jacqueline A. Isaacs

A stochastic goal programming model is developed to aid decision making for CNT-enabled lithium-ion battery manufacturing production and capacity expansion, by considering the balance among economic growth, environmental and human health protection, and sustainability.


2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Ali AlArjani ◽  
Teg Alam

Any bank’s financial management is essential to preparing the assets and liabilities for multiple goals. In this paper, we develop an optimal bank model for the financial management department in the Kingdom of Saudi Arabia. The lexicographic goal programming model was used to formulate the banks’ performance management. In this study, the six goals of one of the leading banks in Saudi Arabia, namely, maximize asset, minimize liability, maximize equity, maximize operating income, maximize net income, and maximizing total goal achievements in the financial statement, were studied. To illustrate the model, we have focused on Al Rajhi Bank’s financial statements as a case study. The data was obtained from the banks’ financial statements. The outcomes of the study exhibited that all goals were accomplished. This proposed model is dynamic because it will help examine the banks’ financial strengths located in the kingdom. As a result, the proposed model can guide banking firms in making decisions and developing strategies to deal with numerous monetary circumstances.


Author(s):  
Saif Wakeel ◽  
Sedat Bingol ◽  
M. Nasir Bashir ◽  
Shafi Ahmad

Selection of the most suitable sustainable material to fulfill the requirements of a product in a specific application is a complex task. Material selection problems are basically multi-criteria decision making problems as selection of the optimal material is based on the evaluation of conflicting criteria. Considering the limitations such as ranking reversal problem of the various multi-criteria decision making methods available in the literature, a combination of two recently developed techniques, i.e. the Goal Programming Model for Best Worst Method and Proximity Indexed Value method, is employed in the present study. This hybrid method was used for selection of the best possible material for manufacturing of a complex automobile part for which F1 race car as advanced automotive and its gearbox casing as sensitive part was used. Available alternative materials considered in the present study are alloys of aluminum, magnesium, titanium, and carbon fiber/epoxy laminate. Whereas, criteria affecting gearbox casing’s performance are tensile strength/density, cost, stiffness, damping capacity, thermal conductivity, and sustainable criteria, such as CO2 emission and recycling energy. Goal Programming Model for Best Worst Method is used to determine weights of the criteria and Proximity Indexed Value method is employed for final selection of material. Furthermore, ranking of alternatives was also supported by other multi-criteria decision making methods namely, range of value, weighted product model, simple additive weighting, the technique for order of preference by similarity to ideal solution, a combined compromise solution, and the multi-attributive border approximation area comparison. Membership degree method was also employed to obtain the final optimal ranking of alternative materials from individual results of applied multi-criteria decision making methods. Besides, sensitivity analysis is done to validate reliability of the results and to determine the most critical evaluation criterion. The result of this study revealed that carbon fiber/epoxy laminate is the best alternative material.


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