Application of Multi Objective Fuzzy Linear Programming in Supply Production Planning Problem

2012 ◽  
Author(s):  
Pandian M. Vasant

The objective of this paper is to establish the usefulness of modified s-curve membership function in a limited supply production planning problem with continuous variables. In this respect, fuzzy parameters of linear programming are modeled by non-linear membership functions such as s-curve function. This paper begins with an introduction and construction of the modified s-curve membership function. A numerical real life example of supply production planning problem is then presented. The computational results show the usefulness of the modified s-curve membership function with fuzzy linear programming technique in optimising individual objective functions, compared to non-fuzzy linear programming approach. Futhermore, the optimal solution helps to conclude that by incorporating fuzziness in a linear programming model through the objective function and constraints, a better level of satisfactory solution will be provided in respect to vagueness, compared to non-fuzzy linear programming.

Author(s):  
Pandian M. Vasant ◽  
R. Nagarajan ◽  
Sazali Yaacob

The modern trend in industrial application problem deserves modeling of all relevant vague or fuzzy information involved in a real decision making problem. In the first part of the paper, some explanations on tri partite fuzzy linear programming approach and its importance have been given. In the second part, the usefulness of the proposed S-curve membership function is established using a real life industrial production planning of a chocolate manufacturing unit. The unit produces 8 products using 8 raw materials, mixed in various proportions by 9 different processes under 29 constraints. A solution to this problem establishes the usefulness of the suggested membership function for decision making in industrial production planning. Key words: Fuzzy linear programming, Satisfactory solution; Decision maker; Implementer; Analyst; Fuzzy constraint; Vagueness.


Author(s):  
PANDIAN M. VASANT

In this paper, we concentrate on two kinds of fuzzy linear programming problems: linear programming problems with only fuzzy resource variables and linear programming problems in which both the resource variables and the technological coefficients are fuzzy numbers. We consider here only the case of fuzzy numbers with modified s-curve membership functions. We propose here the modified s-curve membership function as a methodology for fuzzy linear programming and use it for solving these problems. We also compare the new proposed method with non-fuzzy linear programming optimization method. Finally, we provide real life application examples in production planning and their numerical solutions.


2021 ◽  
Vol 15 ◽  
pp. 8-13
Author(s):  
Mohamed K. Omar ◽  
Muzalna Mohd-Jusoh ◽  
Mohd Omar

This paper considers the hierarchical production planning (HPP) concept to solve a production planning problem in the process industry in a fuzzy environment. The adopted fuzzy HPP consists of two levels in which a fuzzy aggregate production planning (FAPP) model is developed in the first level, and then a fuzzy disaggregate production planning (FDPP) model is developed at the second level. The FAPP was reported by Omar et al. [1] and therefore, this research paper discusses the FDPP model. We formulated the disaggregate model as a fuzzy mixed-integer linear programming model that aims to develop a master production schedule in which numbers of optimal batches are developed in presence of setup time. In addition, we evaluate the performance of the FMILP by comparing its results with a previously reported approach. The findings indicate that significant cost savings were achieved by adopting the fuzzy mathematical programming approach.


Author(s):  
PANDIAN VASANT

Any modern industrial manufacturing unit inevitably faces problems of vagueness in various aspects such as raw material availability, human resource availability, processing capability and constraints and limitations imposed by marketing department. Such a complex problem of vagueness and uncertainty can be handled by the theory of fuzzy linear programming. In this paper, a new fuzzy linear programming based methodology using a modified S-curve membership function is used to solve fuzzy mix product selection problem in Industrial Engineering. Profits and satisfactory level have been computed using fuzzy linear programming approach. Since there are several decisions to be taken, a performance measure has been defined to identify the decision for high level of profit with high degree of satisfaction.


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