Optimizing Diet Problem for Cardiovascular Disease in Fuzzy Environment by Using Multi-Objective Fuzzy Linear Programming

2019 ◽  
Author(s):  
Hossein Eghbali
Keyword(s):  
Cardiovascular Disease ◽  
Linear Programming ◽  
Fuzzy Linear Programming ◽  
Multi Objective ◽  
Fuzzy Environment ◽  
Diet Problem

INTERACTIVE MULTI-OBJECTIVE TRANSPORTATION PLANNING DECISIONS USING FUZZY, LINEAR PROGRAMMING

2008 ◽  
Vol 25 (01) ◽  
pp. 11-31 ◽  
Author(s):  
TIEN-FU LIANG
Keyword(s):  
Linear Programming ◽  
Real World ◽  
Transportation Planning ◽  
Fuzzy Linear Programming ◽  
Total Production ◽  
Multi Objective ◽  
Planning Decisions ◽  
Fuzzy Environment ◽  
Planning Decision ◽  
Systematic Framework

In most real-world situations for transportation planning decision (TPD) problems, environmental coefficients and parameters are imprecise/fuzzy in nature, and the decision maker (DM) generally faces a multi-objective TPD problem in a fuzzy environment. This work develops an interactive fuzzy linear programming (FLP) method for solving TPD problems with fuzzy goals, available supply and forecast demand. The proposed method attempts simultaneously to minimize the total production and transportation costs and the total delivery time with reference to available supply, machine capacities and budget constraints at each source, as well as forecast demand and warehouse space constraints at each destination. In addition, the proposed method provides a systematic framework that facilitates the DM interactively to modify the imprecise data and related parameters until a satisfactory solution is derived. An industrial case is used to demonstrate the feasibility of applying the proposed method to real-world TPD problems. Especially, several significant characteristics of the proposed FLP method are presented in contrast to those of the main TPD methods.

scholarly journals Optimizing Human Diet Problem Based on Price and Taste Using Multi-Objective Fuzzy Linear Programming Approach

2012 ◽  
Vol 2 (2) ◽  
pp. 139-151 ◽  
Author(s):  
Hossein EGHBALI ◽  
Mohammad Ali EGHBALI ◽  
Ali VAHIDIAN KAMYAD
Keyword(s):  
Linear Programming ◽  
Fuzzy Programming ◽  
Fuzzy Linear Programming ◽  
Programming Approach ◽  
Human Diet ◽  
Programming Technique ◽  
Multi Objective ◽  
Two Factors ◽  
Major Factors ◽  
Diet Problem

Low price and good taste of foods are regarded as two major factors for optimal human nutrition. Due to price fluctuations and taste diversity, these two factors cannot be certainly and determinately evaluated. This problem must be viewed from another perspective because of the uncertainty about the amount of nutrients per unit of foods and also diversity of people’s daily needs to receive them.This paper discusses human diet problem in fuzzy environment. The approach deals with multi-objective fuzzy linear programming problem using a fuzzy programming technique for its solution. By prescribing a diet merely based on crisp data, some ofthe realities are neglected. For the same reason, we dealt with human diet problem through fuzzy approach. Results indicated uncertainty about factors of nutrition diet -including taste and price, amount of nutrients and their intake- would affect diet quality, making the proposed diet more realistic.

Multi-Objective Fuzzy Linear Programming for Land Allocation under Different Crops in Bhagwanpur Distributary

2019 ◽  
Vol 6 (04) ◽  
Author(s):  
ASHUTOSH UPADHYAYA
Keyword(s):  
Linear Programming ◽  
Crop Production ◽  
Fuzzy Linear Programming ◽  
Programming Method ◽  
Command Area ◽  
Linear Programming Method ◽  
Net Return ◽  
Multi Objective ◽  
Labour Requirement ◽  
Canal Command Area

A study was undertaken in Bhagwanpur distributary of Vaishali Branch Canal in Gandak Canal Command Area, Bihar to optimally allocate land area under different crops (rice and maize in kharif, wheat, lentil, potato in rabi and green gram in summer) in such a manner that maximizes net return, maximizes crop production and minimizes labour requirement employing simplex linear programming method and Multi-Objective Fuzzy Linear Programming (MOFLP) method. Maximum net return, maximum agricultural production, and minimum labour required under defined constraints (including 10% affinity level of farmers to rice and wheat crops) as obtained employing Simplex method were ` 3.7 × 108, 5.06 × 107 Kg and 66,092 man-days, respectively, whereas Multi-Objective Fuzzy Linear Programming (MOFLP) method yielded compromised solution with net return, crop production and labour required as ` 2.4 × 108, 3.3 × 107Kg and 1,79,313 man-days, respectively. As the affinity level of farmers to rice and wheat crops increased from 10% to 40%, maximum net return and maximum production as obtained from simplex linear programming method and MOFLP followed a decreasing trend and minimum labour required followed an increasing trend. MOFLP may be considered as one of the best capable ways of providing a compromised solution, which can fulfill all the objectives at a time.

Optimizing Human Diet Problem with Fuzzy Price Using Fuzzy Linear Programming Approach

2011 ◽  
Vol 10 (6) ◽  
pp. 594-598 ◽  
Author(s):  
Mustafa Mamat ◽  
Yeni Rokhayati ◽  
Noor Maizura Mohamad Noor ◽  
Ismail Mohd
Keyword(s):  
Linear Programming ◽  
Fuzzy Linear Programming ◽  
Programming Approach ◽  
Human Diet ◽  
Linear Programming Approach ◽  
Diet Problem

A Different Approach for Solving the Shortest Path Problem Under Mixed Fuzzy Environment

2020 ◽  
Vol 9 (2) ◽  
pp. 132-161 ◽  
Author(s):  
Ranjan Kumar ◽  
Sripati Jha ◽  
Ramayan Singh
Keyword(s):  
Linear Programming ◽  
Shortest Path ◽  
Path Length ◽  
Real Life ◽  
Shortest Path Problem ◽  
Fuzzy Linear Programming ◽  
Fuzzy Membership ◽  
Fuzzy Membership Function ◽  
Membership Functions ◽  
Fuzzy Environment

The authors present a new algorithm for solving the shortest path problem (SPP) in a mixed fuzzy environment. With this algorithm, the authors can solve the problems with different sets of fuzzy numbers e.g., normal, trapezoidal, triangular, and LR-flat fuzzy membership functions. Moreover, the authors can solve the fuzzy shortest path problem (FSPP) with two different membership functions such as normal and a fuzzy membership function under real-life situations. The transformation of the fuzzy linear programming (FLP) model into a crisp linear programming model by using a score function is also investigated. Furthermore, the shortcomings of some existing methods are discussed and compared with the algorithm. The objective of the proposed method is to find the fuzzy shortest path (FSP) for the given network; however, this is also capable of predicting the fuzzy shortest path length (FSPL) and crisp shortest path length (CSPL). Finally, some numerical experiments are given to show the effectiveness and robustness of the new model. Numerical results show that this method is superior to the existing methods.

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