Operational budgeting using fuzzy goal programming

Having an efficient budget normally has different advantages such as measuring the performance of various organizations, setting appropriate targets and promoting managers based on their achievements. However, any budgeting planning requires prediction of different cost components. There are various methods for budgeting planning such as incremental budgeting, program budgeting, zero based budgeting and performance budgeting. In this paper, we present a fuzzy goal programming to estimate operational budget. The proposed model uses fuzzy triangular as well as interval number to estimate budgeting expenses. The proposed study of this paper is implemented for a real-world case study in province of Qom, Iran and the results are analyzed

Preemptive Fuzzy Goal Programming in Fuzzy Environments

There are a variety of efficient approaches to solve crisp multiple objective decision making problems. However in the real life the input data may not be precisely determined because of the incomplete information. This paper deals with a method which can be applied to solve fuzzy multi objective production marketing problems

The fuzzy goal programming approach to production planning of intermediate gear spare parts: a case study

Production planning has an important role in the company's business processes. A company engaged in the manufacture of intermediate gear parts has a problem in optimizing its production system. The production planning system that occurs is still based on predictions from decision-makers. This study aims to optimize the production planning system to maximize the 15T intermediate gear spare parts' production capacity and the 30T intermediate gear spare parts. Optimization of production planning uses the fuzzy goal programming method to optimize objectives based on existing constraints such as working hours, profit tolerance values, and demand tolerance values. The results showed that the use of fuzzy goal programming was able to increase the production level by 2.765, with an increase in profit of 2.57%. Fuzzy goal programming implementation provides an optimal solution in increasing profits in accordance with company goals based on the constraints that occur

Using the hybrid fuzzy goal programming model and hybrid genetic algorithm to solve a multi-objective location routing problem for infectious waste disposal

Purpose: Disposal of infectious waste remains one of the most serious problems in the social and environmental domains of almost every nation. Selection of new suitable locations and finding the optimal set of transport routes to transport infectious waste, namely location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Design/methodology/approach: Due to the complexity of this problem, location routing problem for a case study, forty hospitals and three candidate municipalities in sub-Northeastern Thailand, was divided into two phases. The first phase is to choose suitable municipalities using hybrid fuzzy goal programming model which hybridizes the fuzzy analytic hierarchy process and fuzzy goal programming. The second phase is to find the optimal routes for each selected municipality using hybrid genetic algorithm which hybridizes the genetic algorithm and local searches including 2-Opt-move, Insertion-move and ?-interchange-move. Findings: The results indicate that the hybrid fuzzy goal programming model can guide the selection of new suitable municipalities, and the hybrid genetic algorithm can provide the optimal routes for a fleet of vehicles effectively. Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.Peer Reviewe

PENYELESAIAN MASALAH PERENCANAAN PRODUKSI DENGAN PENDEKATAN FUZZY GOAL PROGRAMMING (Studi Kasus: Perusahaan Kaos Kaki di Kabupaten Majalengka)

Masalah perencanaan produksi yang dialami oleh sebuah perusahaan biasanya disebabkan oleh sistem perencanaan produksi yang kurang baik. Sistem perencanaan produksi yang baik akan memberikan kepuasan terhadap perusahaan dengan target yang diingin dan juga dengan bahan baku yang tersedia. Pada penelitian ini, masalah perencanaan produksiakan diselesaikan dengan model fuzzy goal programming. Model fuzzy goal programming mencari solusi optimal berdasarkan target yang diinginkan perusahaan. Hasil implementasi model fuzzy goal programming pada masalah perencanaan produksi kaos kaki di sebuah perusahaan di Kabupaten Majalengka menunjukkan bahwa dengan menggunakan model fuzzy goal programming hasil yang diperoleh lebih optimal dibandingkan dengan menggunakan model goal programming. Production planning problems often occur because ofa poor production system planning. A good production planning system will give a satisfaction for the companiessince their targets and their available raw materials are considered. In this research, the problem of production planning is solved by the fuzzy goal programming model. The fuzzy goal programming model finds optimal solutions based on the desired target of the company. We implemented the model to the problem of socks production planning in a company in Majalengka.The computational results show that we obtain more optimal solution compare with the solution of goal programming model

Fuzzy Goal Programming Procedure to Bilevel Multiobjective Linear Fractional Programming Problems

This paper presents a fuzzy goal programming (FGP) procedure for solving bilevel multiobjective linear fractional programming (BL-MOLFP) problems. It makes an extension work of Moitra and Pal (2002) and Pal et al. (2003). In the proposed procedure, the membership functions for the defined fuzzy goals of the decision makers (DMs) objective functions at both levels as well as the membership functions for vector of fuzzy goals of the decision variables controlled by first-level decision maker are developed first in the model formulation of the problem. Then a fuzzy goal programming model to minimize the group regret of degree of satisfactions of both the decision makers is developed to achieve the highest degree (unity) of each of the defined membership function goals to the extent possible by minimizing their deviational variables and thereby obtaining the most satisfactory solution for both decision makers. The method of variable change on the under- and over-deviational variables of the membership goals associated with the fuzzy goals of the model is introduced to solve the problem efficiently by using linear goal programming (LGP) methodology. Illustrative numerical example is given to demonstrate the procedure

Imprecise WareHouse Space in Aggregate Production Planning Using Fuzzy Goal Programming

Considering the fluctuating market demands with variable storage capacity and available production capacity, this study examines a number of workable techniques for modeling multiproduct aggregate production planning problems with fuzzy numbers. The suggested method makes use of factors including; inventory levels, labor levels, overtime, backordering levels, workforce capacity, machine capacity, and fuzzy warehouse capacity in an effort to reduce operating costs, reduce production waste, and increase capacity utilization rate. With the aid of this formulation and interpretation, a fuzzy multiproduct aggregate production planning model is developed. Finally, the study's conclusions were arrived at using information provided by Rich Pharmaceuticals Ltd. using Lingo version 18 software (RPL).and it uses parametric programming, best balancing, and interactive techniques to give solutions that can be adjusted to fit a variety of decision-making circumstances