A particular simplex algorithm to solve fuzzy lexicographic multi-objective linear programming problems and their sensitivity analysis on the priority of the fuzzy objective functions

2014 ◽  
Vol 26 (5) ◽  
pp. 2333-2358 ◽  
Author(s):  
Reza Ezzati ◽  
Esmaile Khorram ◽  
Ramin Enayati
Keyword(s):  
Sensitivity Analysis ◽  
Linear Programming ◽  
Simplex Algorithm ◽  
Objective Functions ◽  
Multi Objective ◽  
Linear Programming Problems

scholarly journals Modeling of Gauss Elimination Technique and AHA Simplex Algorithm for Multi-objective Linear Programming Problems

2020 ◽  
pp. 1-14
Author(s):  
Sanjay Jain ◽  
Adarsh Mangal
Keyword(s):  
Linear Programming ◽  
Numerical Solution ◽  
Objective Function ◽  
Programming Problem ◽  
Linear Programming Problem ◽  
Simplex Algorithm ◽  
Multi Objective ◽  
Linear Objective Function ◽  
Gauss Elimination ◽  
Linear Programming Problems

In this research paper, an effort has been made to solve each linear objective function involved in the Multi-objective Linear Programming Problem (MOLPP) under consideration by AHA simplex algorithm and then the MOLPP is converted into a single LPP by using various techniques and then the solution of LPP thus formed is recovered by Gauss elimination technique. MOLPP is concerned with the linear programming problems of maximizing or minimizing, the linear objective function having more than one objective along with subject to a set of constraints having linear inequalities in nature. Modeling of Gauss elimination technique of inequalities is derived for numerical solution of linear programming problem by using concept of bounds. The method is quite useful because the calculations involved are simple as compared to other existing methods and takes least time. The same has been illustrated by a numerical example for each technique discussed here.

scholarly journals Fuzzy Multi Objective Linear Programming Problem with Imprecise Aspiration Level and Parameters

2015 ◽  
Vol 5 (2) ◽  
pp. 81-86 ◽  
Author(s):  
Zahra Shahraki ◽  
Mehdi Allahdadi ◽  
Hassan Mishmast Nehi
Keyword(s):  
Linear Programming ◽  
Programming Problem ◽  
Linear Programming Problem ◽  
Aspiration Level ◽  
Membership Functions ◽  
Objective Functions ◽  
Multi Objective ◽  
Fuzzy Goals ◽  
Linear Programming Problems

This paper considers the multi-objective linear programming problems with fuzzygoal for each of the objective functions and constraints. Most existing works deal withlinear membership functions for fuzzy goals. In this paper, exponential membershipfunction is used.

scholarly journals Comments on Modeling of Gauss Elimination Technique and AHA Simplex Algorithm for Multi-objective Linear Programming Problems by Sanjay Jain and Adarsh Mangal

2020 ◽  
Vol 06 (09) ◽  
pp. 94-96
Author(s):  
Chandra Sen
Keyword(s):  
Linear Programming ◽  
Objective Function ◽  
Simplex Method ◽  
Simplex Algorithm ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Excellent Research ◽  
Gauss Elimination ◽  
Linear Programming Problems ◽  
Averaging Techniques

An excellent research contribution was made by Sanjay and Adarsh in using Gauss Elimination Technique and AHA simplex method for solving multi-objective optimization (MOO) problems. The method was applied for solving MOO problems using Chandra Sen's technique and several other averaging techniques. The formulation of multi-objective function in the averaging techniques was not perfect. The example was also not appropriate.

IDENTIFICATION OF REDUNDANT OBJECTIVE FUNCTIONS IN MULTI-OBJECTIVE STOCHASTIC FRACTIONAL PROGRAMMING PROBLEMS

2006 ◽  
Vol 23 (02) ◽  
pp. 155-170 ◽  
Author(s):  
V. CHARLES ◽  
D. DUTTA
Keyword(s):  
Linear Programming ◽  
Fractional Programming ◽  
Solution Procedure ◽  
Objective Functions ◽  
Non Linear Programming ◽  
Multi Objective ◽  
Main Emphasis ◽  
Non Linear ◽  
Linear Programming Problems

Redundancy in constraints and variables are usually studied in linear, integer and non-linear programming problems. However, main emphasis has so far been given only to linear programming problems. In this paper, an algorithm that identifies redundant objective functions in multi-objective stochastic fractional programming problems is provided. A solution procedure is also illustrated. This reduces the number of objective functions in cases where redundant objective functions exist.

Fuzzy multi-objective decision making approach for nuclear power plant installation

2020 ◽  
Vol 39 (5) ◽  
pp. 6339-6350
Author(s):  
Esra Çakır ◽  
Ziya Ulukan
Keyword(s):  
Linear Programming ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Energy Supply ◽  
Energy Demand ◽  
Nuclear Power ◽  
Power Plants ◽  
Total Duration ◽  
Objective Functions ◽  
Multi Objective

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.

Solving Fully Fuzzy Multi-Objective Linear Programming Problems

2012 ◽  
Vol 3 (4) ◽  
pp. 1-6 ◽  
Author(s):  
M.Jayalakshmi M.Jayalakshmi ◽  
◽  
P.Pandian P.Pandian
Keyword(s):  
Linear Programming ◽  
Multi Objective ◽  
Linear Programming Problems

Optimal design of a parallel robotic gripper using enhanced multi-objective ant lion optimizer with a sensitivity analysis approach

2020 ◽  
Vol 40 (5) ◽  
pp. 703-721
Author(s):  
Golak Bihari Mahanta ◽  
Deepak BBVL ◽  
Bibhuti B. Biswal ◽  
Amruta Rout
Keyword(s):  
Sensitivity Analysis ◽  
Distribution Function ◽  
Design Parameters ◽  
Objective Functions ◽  
Content Type ◽  
Multi Objective ◽  
The Past ◽  
Design Variables ◽  
Pick And Place ◽  
Ant Lion

Purpose From the past few decades, parallel grippers are used successfully in the automation industries for performing various pick and place jobs due to their simple design, reliable nature and its economic feasibility. So, the purpose of this paperis to design a suitable gripper with appropriate design parameters for better performance in the robotic production systems. Design/methodology/approach In this paper, an enhanced multi-objective ant lion algorithm is introduced to find the optimal geometric and design variables of a parallel gripper. The considered robotic gripper systems are evaluated by considering three objective functions while satisfying eight constraint equations. The beta distribution function is introduced for generating the initial random number at the initialization phase of the proposed algorithm as a replacement of uniform distribution function. A local search algorithm, namely, achievement scalarizing function with multi-criteria decision-making technique and beta distribution are used to enhance the existing optimizer to evaluate the optimal gripper design problem. In this study, the newly proposed enhanced optimizer to obtain the optimum design condition of the design variables is called enhanced multi-objective ant lion optimizer. Findings This study aims to obtain optimal design parameters of the parallel gripper with the help of the developed algorithms. The acquired results are investigated with the past research paper conducted in that field for comparison. It is observed that the suggested method to get the best gripper arrangement and variables of the parallel gripper mechanism outperform its counterparts. The effects of the design variables are needed to be studied for a better design approach concerning the objective functions, which is achieved by sensitivity analysis. Practical implications The developed gripper is feasible to use in the assembly operation, as well as in other pick and place operations in different industries. Originality/value In this study, the problem to find the optimum design parameter (i.e. geometric parameters such as length of the link and parallel gripper joint angles) is addressed as a multi-objective optimization. The obtained results from the execution of the algorithm are evaluated using the performance indicator algorithm and a sensitivity analysis is introduced to validate the effects of the design variables. The obtained optimal parameters are used to develop a gripper prototype, which will be used for the assembly process.

scholarly journals Assignment model with multi-objective linear programming for allocating choice ranking using recurrent neural network

2021 ◽  
Author(s):  
Zahra Sadat Mirzazadeh ◽  
Javad Banihassan ◽  
Amin Mansoori
Keyword(s):  
Neural Network ◽  
Linear Programming ◽  
Recurrent Neural Network ◽  
Absolute Priority ◽  
Multi Objective ◽  
Assignment Method ◽  
Assignment Model ◽  
Decision Attributes ◽  
Linear Programming Problems ◽  
Linear Assignment

Classic linear assignment method is a multi-criteria decision-making approach in which criteria are weighted and each rank is assigned to a choice. In this study, to abandon the requirement of calculating the weight of criteria and use decision attributes prioritizing and also to be able to assign a rank to more than one choice, a multi-objective linear programming (MOLP) method is suggested. The objective function of MOLP is defined for each attribute and MOLP is solved based on absolute priority and comprehensive criteria methods. For solving the linear programming problems we apply a recurrent neural network (RNN). Indeed, the Lyapunov stability of the model is proved. Results of comparing the proposed method with TOPSIS, VICOR, and MOORA methods which are the most common multi-criteria decision schemes show that the proposed approach is more compatible with these methods.

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