Tunjo Perić

Vendor selection and supply quantities determination in a bakery by AHP and fuzzy multi-criteria programming

One of the possible conceptions for the survival in a turbulent world market is a chain cooperation among the producer, his suppliers and customers, according to the concept of supply chain management. The problem of vendor selection and determination of material quantities supplied is one of the most important activities in the supply chain. The purpose of this article is to propose a model for vendor selection and determination of supply quotas in the area of flour supply by using the analytic hierarchy process (AHP) and multi-objective linear programming (LP) model solved by fuzzy LP method, based on the decision-making in a fuzzy environment, and to point to the advantages of the proposed model in comparison to some other vendor selection and supply quantity determination models. The proposed model applied in the concrete problem of vendor selection and determination of supply quotas proved to be very efficient in determining the priority of alternatives, taking into account all the criteria and sub-criteria, as well as in defining criteria weights that express the decision-makers preferences, which allows a simple sensitivity analysis of the obtained solutions.

Multiproduct Vendor Selection with Volume Discounts as the Fuzzy Multi-Objective Programming Problem

Vendor selection in supply chain is a multi-criteria problem that involves a number of quantitative and qualitative factors. This paper deals with a concrete problem of flour purchase by a company that manufactures bakery products. The selection process is driven by the price, reliability and quality objectives of the buyer and is subject to the capacity constraints of the vendors in the situation where all suppliers offer several kinds of flour (multiproduct situation). Vendors often offer quantity discounts, i.e. the purchasing price of flour depends on the quantity ordered. The multiproduct situation complicates the mathematical formulation of the problem and in this context it is much more convenient to consider the discounts of the money volume of business with every vendor. This problem has been solved using an integration of analytic hierarchy process (AHP), weighted sum model (WSM) and fuzzy multi-objective mixed-integer programming to define the optimum quantities among the selected suppliers.

A new iterative method for solving multiobjective linear programming problem

In the paper we present a new iterative method for solving multiobjective linear programming problems with an arbitrary number of decision makers. The method is based on the principles of game theory. Each step of the method yields a unique solution which respects the aspirations of decision makers within the frame of given possibilities. Each decision maker is assigned an objective indicator which shows the reality of his aspiration and which may be used to define the strategy for the next step. The method can be easily extended to general (nonlinear) multiobjective programming problems but the numerical application would require further research on computational methods.

Comparative analysis of application efficiency of two iterative multi objective linear programming methods (MP method and STEM method)

In this paper we consider a production plan optimization problem for a company that produces textile products. The problem is solved using two iterative methods: a new method based on the cooperative game theory (MP method) and the well-known STEM method. Their application efficiency and the solutions obtained are compared. For this purpose we use four groups of criteria: (1) the general characteristics of the method (2) the criteria from the standpoint of the decision makers, (3) the criteria from the perspective of the analysts, and (4) the ‘economic’ criteria. The analysis indicates that both methods are highly efficient for solving this kind of production plan optimization problems. However, the decision-makers preferred the MP method.

OPTIMIZATION OF PRODUCTION PLAN IN THE METAL INDUSTRY BY THE USE OF DE NOVO PROGRAMMING

Production plan optimization is one of the most important activities of the production companies in theendeavours to ensure competitive advantages. In preparing the production plan numerous factors are necessary tobe included. The problem of creating the production plan is getting more complicated when the production inputsoccur at variable prices. In this paper the application of De Novo programming model is investigated in theproduction plan optimization in the metal industry. The efficiency of the proposed model is examined on the case of acompany that produces metal containers. The obtained results indicate the high application efficiency of the modelbased on De Novo programming in the production plan optimization in the metal producing companies.

Vendor Selection and Supply Quotas Determination by Using a New Multi-Objective Programming Method Based on Cooperative Game Theory

Abstract Background: Vendor selection and supply quotas determination is one of the most important issues in the purchasing process in manufacturing. In many situations to solve this problem it is necessary to use the operations research methods. Objectives: This paper proposes a new methodology for vendor selection and determination of supplied quotas. The work investigates the problem of flour purchase by a company that manufactures bakery products. Methods/Approach: The problem is solved by using the model that combines a revised weighting method, and a multiple objective programming method based on game theory. The revised weighting method is used to determine the objective function coefficients, and a multiple objective programming method is used to select vendors and to determine supply quotas from the selected vendors. For selection of vendors and determination of quantities supplied by individual vendors three complex criteria are used: (1) purchasing costs, (2) product quality, and (3) vendor reliability. Results: The proposed methodology has numerous strengths, such as an efficient reduction of complex criteria functions to simple ones and efficient using of a new multiple objective programming methods based on cooperative game theory. Conclusions: The main advantage of the proposed approach is its efficiency and simplicity.

An Application of the MP Method for Solving the Problem of Distribution

In this paper, we present an application of a method for solving the multi-objective programming problem (the MP method), which was introduced in [1]. This method is used to solve the problem of distribution (te problem of cost/profit allocation). The method is based on the principles of cooperative games and linear programming. In the paper, we consider the standard case (proportional distribution) and the generalized case in which the basic ideas of coalitions have been incorporated. The presented theory is applied and explained on an investment model for economic recovery.

Statistical Analysis of Causality between Capital Structure and Firm Profitability: Evidence from Bosnia and Herzegovina

Abstract This research is designed to examine the relationship between the capital structure and profitability of non-financial firms in Bosnia and Herzegovina during the ten years period, from 2003-2012. The goal is to prove the existence of the relationship between the firm’s capital structure choice and its profitability. The analysis is extended by including the debt structure and differentiating between the types of debt such as the long-term and the short-term ones. Canonical correlation and multiple regression analysis are used. The results of the multivariate canonical correlation analysis provide support to a hypothesis that the capital structure and profitability have statistically significant relationships. Furthermore, the findings provide support that firms develop different patterns of profitability depending on the capital structure choice. We found that an increasing proportion of short-term debt and long-term debt in the overall liability of the firm reduces its profitability.

Optimization of Industrial Production of Feed Blends as Multiple Criteria Programming Problem

Optimization of industrial production of feed blends in terms of their nutritive value and in terms of economic criteria can be carried out by application of mathematical optimization methods. The benefit of application of these methods is fast and efficient solution for the optimal combination of ingredients considering the nutritive needs of animals and constraints in their availability. Unlike the standard problem of feed where the requirements for basic nutrients have to be met at minimised costs and which is solved mainly by linear programming, the authors introduce also the goals of meal quality where different requirements of decision makers are modelled by multiple-criteria linear programming.

Fabric Cutting as the Multiple Criteria Programming Problem

In this paper authors indicate, by means of a concrete example, that it is possible to apply the method of multiple criteria integer linear programming method in dealing with the problem of determining an optimal plan for fabric cutting optimization. The following are being shown: 1) Selection of the criteria for optimization of fabric cutting, 2) Setting the problem of determining an optimal plan of fabric cutting, 3) Setting the model of multiple criteria linear integer programming in finding solution to a given problem (4) The solutions are obtained applying the methods of weight coefficients and the method of satisfactory goals.