Applying interactive fuzzy multi-objective linear programming to transportation planning decisions

2006 ◽  
Vol 27 (1) ◽  
pp. 107-126 ◽  
Author(s):  
Tien-Fu Liang
2008 ◽  
Vol 25 (01) ◽  
pp. 11-31 ◽  
Author(s):  
TIEN-FU LIANG

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.


2020 ◽  
Vol 39 (5) ◽  
pp. 6339-6350
Author(s):  
Esra Çakır ◽  
Ziya Ulukan

Due to the increase in energy demand, many countries suffer from energy poverty because of insufficient and expensive energy supply. Plans to use alternative power like nuclear power for electricity generation are being revived among developing countries. Decisions for installation of power plants need to be based on careful assessment of future energy supply and demand, economic and financial implications and requirements for technology transfer. Since the problem involves many vague parameters, a fuzzy model should be an appropriate approach for dealing with this problem. This study develops a Fuzzy Multi-Objective Linear Programming (FMOLP) model for solving the nuclear power plant installation problem in fuzzy environment. FMOLP approach is recommended for cases where the objective functions are imprecise and can only be stated within a certain threshold level. The proposed model attempts to minimize total duration time, total cost and maximize the total crash time of the installation project. By using FMOLP, the weighted additive technique can also be applied in order to transform the model into Fuzzy Multiple Weighted-Objective Linear Programming (FMWOLP) to control the objective values such that all decision makers target on each criterion can be met. The optimum solution with the achievement level for both of the models (FMOLP and FMWOLP) are compared with each other. FMWOLP results in better performance as the overall degree of satisfaction depends on the weight given to the objective functions. A numerical example demonstrates the feasibility of applying the proposed models to nuclear power plant installation problem.


2012 ◽  
Vol 3 (4) ◽  
pp. 1-6 ◽  
Author(s):  
M.Jayalakshmi M.Jayalakshmi ◽  
◽  
P.Pandian P.Pandian

2019 ◽  
Vol 6 (04) ◽  
Author(s):  
ASHUTOSH UPADHYAYA

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.


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