A Compromise Allocation Based on the Individual Mixed Allocations in Multivariate Stratified Sampling : A Goal Programming Approach

2012 ◽  
Vol 64 (1-2) ◽  
pp. 97-114
Author(s):  
Rahul Varshney ◽  
M.J. Ahsan ◽  
Athar H. Ansari
Keyword(s):  
Goal Programming ◽  
Stratified Sampling ◽  
Programming Approach ◽  
Compromise Allocation ◽  
Multivariate Stratified Sampling ◽  
The Individual

scholarly journals A fuzzy goal programming approach in stochastic multivariate stratified sample surveys

2013 ◽  
Vol 31 (1) ◽  
pp. 80 ◽  
Author(s):  
Neha Gupta ◽  
Irfan Ali ◽  
Shafiullah ◽  
Abdul Bari
Keyword(s):  
Goal Programming ◽  
Computational Procedure ◽  
Fuzzy Goal Programming ◽  
Programming Approach ◽  
Membership Functions ◽  
Compromise Allocation ◽  
Multivariate Stratified Sampling ◽  
Non Linear ◽  
Fuzzy Goal ◽  
The Individual

This paper deals with fuzzy goal programming (FGP) approach to stochastic multivariate stratified sampling with non linear objective function and probabilistic non linear cost constraint which is formulated as a multiobjective non linear programming problem (MONLPP). In the model formulation of the problem, we first determine the individual best solution of the objective functions subject to the system constraints and construct the non linear membership functions of each objective. The non linear membership functions are then transformed into equivalent linear membership functions by first order Taylor series at the individual best solution point. Fuzzy goal programming approach is then used to achieve maximum degree of each of the membership goals by minimizing negative deviational variables and finally obtain the compromise allocation. A numerical example is presented to illustrate the computational procedure of the proposed approach.

scholarly journals Neutrosophic fuzzy goal programming approach in selective maintenance allocation of system reliability

2021 ◽  
Author(s):  
Murshid Kamal ◽  
Umar Muhammad Modibbo ◽  
Ali AlArjani ◽  
Irfan Ali
Keyword(s):  
Goal Programming ◽  
System Reliability ◽  
Programming Approach ◽  
Reliability Optimization ◽  
Numerical Illustration ◽  
Programming Technique ◽  
Compromise Allocation ◽  
Selective Maintenance ◽  
System Reliability Optimization ◽  
Fuzzy Parameters

AbstractSelective maintenance problem plays an essential role in reliability optimization decision-making problems. Systems are a configuration of several components, and there are situations the system needs small intervals or break for maintenance actions, during the intervals expert carried out the maintenance actions to replace or repair the deteriorated components of the systems. Because of the uncertainty associated with the component’s operational time, failure, and next mission duration create a new challenge in determining optimal components allocation and evaluating future missions successfully. In this paper, a multi-objective selective maintenance allocation problem is formulated with fuzzy parameters under neutrosophic environment. A new defuzzification technique is introduced based on beta distribution to convert fuzzy parameters into crisp values. The neutrosophic goal programming technique is used to determine the compromise allocation of replaceable and repairable components based on the system reliability optimization. A numerical illustration is used to validate the model and ascertain its effectiveness. The result is compared with two other approaches and found to be better. The method is flexible and straightforward and can be solved using any available commercial packages. The extension of the concept can be useful to other complex system reliability optimization.

scholarly journals Interactive Fuzzy Goal Programming approach in multi-response stratified sample surveys

2016 ◽  
Vol 26 (2) ◽  
pp. 241-258 ◽  
Author(s):  
Neha Gupta ◽  
Irfan Ali ◽  
Abdul Bari
Keyword(s):  
Linear Programming ◽  
Programming Problem ◽  
Goal Programming ◽  
Linear Programming Problem ◽  
Real Data ◽  
Fuzzy Goal Programming ◽  
Programming Approach ◽  
Compromise Allocation ◽  
Fuzzy Goal ◽  
Interactive Fuzzy Goal Programming

In this paper, we applied an Interactive Fuzzy Goal Programming (IFGP) approach with linear, exponential and hyperbolic membership functions, which focuses on maximizing the minimum membership values to determine the preferred compromise solution for the multi-response stratified surveys problem, formulated as a Multi- Objective Non Linear Programming Problem (MONLPP), and by linearizing the nonlinear objective functions at their individual optimum solution, the problem is approximated to an Integer Linear Programming Problem (ILPP). A numerical example based on real data is given, and comparison with some existing allocations viz. Cochran?s compromise allocation, Chatterjee?s compromise allocation and Khowaja?s compromise allocation is made to demonstrate the utility of the approach.

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