Implementation of Optimum Resource Allocation by Fuzzy Goal Programming: The Case of Higher Education System (original) (raw)

Bulanik Amaç Programlama Yardimi İle Optimum Kaynak Tahsi̇sati : Yüksek Eği̇ti̇m Si̇stemi̇ Uygulamasi

Pamukkale Universitesi Muhendislik Bilimleri Dergisi, 2003

The Goal Programming, which is using to solve the multiple objective decision problems, has wide and great potential among other methods targeting maximization or minimization of goals. The main aim of the goal programming is to minimize the biases from each objective, instead of optimization of goals. Goal Programming algorithms, as originally developed by Charnels, attempts to achieve as many of these goals possible by minimizing deviation variables from the goal levels, depending on their relative weights. This minimization process has been forming in two categories, which involves preemptive and weighted techniques. In this study, Fuzzy Goal Programming has used to determine optimum allocation of education equipment such as computer and laptop to the faculty members and officers at different level of positions.

Academic Personnel Planning Problems in University Management System via Fuzzy Goal Programming with Penalty Functions

2015

This article demonstrates how the genetic algorithm (GA) approach can efficiently be used to the penalty function based fuzzy goal programming (FGP) formulation for modelling and solving academic resource planning problems in University management system. A demonstrative case example of the University of Kalyani, West Bengal (W.B), India is considered to expound the potential use of the approach. The proposed model is compared with the conventional FGP solution of the problem.

Fuzzy Goal Programming Problem Based on Minmax Approach for Optimal System Design

Alphanumeric Journal, 2018

Every system in nature evolved in order to carry on their existence and reach their targets with minimal losses. The fundamental condition of a system's success lies on making the correct decision by evaluating multiple, complicated, and conflicting goals based on the present constraints. Many mathematical programming problems are makeup of objective functions combined by the decision maker based on the constrains. This study investigates how an optimal design can be reached based on Minmax approach. Goal Programming and a Fuzzy Goal Programming known as MA approach are used in this study. The solution of a problem organized as a Multiple De novo programming in order to determine the resource amounts for a business in handcrafts is carried out based on these two approaches. Budget constrain is organized as a goal to solve the problem based on MA approach, and a solution is proposed accordingly. The acquired results suggest that the solution results of Minmax Goal Programming and MA approach are the same.

An integrated multiple criteria decision making approach for resource allocation in higher education

International Journal of Innovation and Learning, 2007

Resource allocation is one of the major decision problems arising in higher education. Resources must be allocated optimally in such a way that the performance of universities can be improved. This paper applies an integrated multiple criteria decision making approach to the resource allocation problem. In the approach, the analytic hierarchy process (AHP) is first used to determine the priority or relative importance of proposed projects with respect to the goals of the universities. Then, the goal programming (GP) model incorporating the constraints of AHP priority, system, and resource is formulated for selecting the best set of projects without exceeding the limited available resources. The projects include "hardware" (tangible university's infrastructures), and "software" (intangible effects that can be beneficial to the university, its members, and its students). In this paper, two commercial packages are used: Expert Choice for determining the AHP priority ranking of the projects, and LINDO for solving the GP model. 2

Goal Programming in a Fuzzy Environment

Decision Sciences, 1980

This paper illustrates the application of "fuzzy subsets" concepts to goal programming in a fuzzy environment. In contrast to a typical goal-programming problem, the goals are stated imprecisely when the decision environment is fuzzy. The paper first considers a fuzzy goal-programming problem with multiple goals having equal weights associated with them. A solution approach based on linear programming is developed. Next, the solution approach is extended to the case where unequal fuzzy weights are associated with multiple goals. Numerical examples are provided for both cases to illustrate the solution procedure.

A preemptive goal programming for allocating students into academic departments of a faculty

2016

A goal programming model is built to optimize the allocation of students into academic departments of a faculty. The goal programming model takes into account the limits of space capacity, financial allocation, the number of instructors and affirmative action quotas as goal constraints that are required to be fulfilled. Each constraint has a priority level and a weight attached. This goal programming model is then applied to the Faculty of Science and Technology, Universiti Kebangsaan Malaysia. The results of the preemptive goal programming model are then compared to that of the current allocation using the weighted mean absolute percentage error. The successful application demonstrates the ability of the goal programming model to comply with the student intake requirement and goal constraints of the academic departments.

A priority-based goal programming method for solving academic personnel planning problems with interval-valued resource goals in university management system

International Journal of Applied Management Science, 2012

This chapter describes a GP procedure for modelling and solving academic resource planning problems in university management system with interval data uncertainty. In the proposed approach, the interval goals are first converted into the standard goals by using interval arithmetic technique. Certain objectives having the characteristics of fractional programming are transformed into linear goals by using linearization approach to solve the problem by employing linear GP methodology. In the model formulation of the problem, both the aspects of GP, minsum and minmax approaches, are addressed to construct the goal achievement function for minimising the possible regret towards achieving the goal values within the target intervals specified by the DM in the decision making environment. The potential use of the approach is illustrated by a case example. The model solution is compared with the solutions of the models studied previously.

Fuzzy Goal Programming Approach for Resource Allocation in an NGO Operation

2018

Diabetes is a major health challenge in India. The lifetime cost of treatment in the disease management is humongous. India is presently lacking at infrastructure and resources to meet the demand created by the sudden surge of the disease. This situation makes it imperative to optimally allocate the resources so that the treatment can be made available to a maximum number of patients at affordable cost. This paper uses fuzzy goal programming with exponential membership function for resource allocation. The human and financial resources are described with fuzzy conditions for determining the future strategies for unknown situations. A fuzzy goal programming model is demonstrated using the case study of an NGO working in the area of awareness and treatment of diabetes in Varanasi.