In this paper, a Multi-Choice Stochastic Bi-Level Programming Problem (MCSBLPP) is considered where all the parameters of constraints are followed by normal distribution. The cost coefficients of the objective functions are multi-choice types. At first, all the probabilistic constraints are transformed into deterministic constraints using stochastic programming approach. Further, a general tran...

optimal allocation of water resources is an essential service in agriculture that must be considered by farmers. one of the most significant factors in optimal allocation of water resources in agriculture is to define optimal farm cropping pattern. in this study, in order to determine optimal cropping pattern and water resources allocation in central district of mashhad city (toos village), the...

Abstract It has been shown that evolutionary algorithms are able to construct suitable search strategies for classes of Constraint Satisfaction Problems (CSPs) in Programming. This paper is an explanation the use multi-objective optimisation contrast simple additive weighting techniques with a view develop CSPs. A hierarchical scheme employed select candidate strategy from Pareto frontier final...

<p style='text-indent:20px;'>We consider a complex multi-objective programming problem (CMP). In order to establish the optimality conditions of (CMP), we introduce several properties optimal efficient solutions and scalarization techniques. Furthermore, certain parametric dual model is discussed, their duality theorems are proved.</p>

Normal Boundary Intersection (NBI) is traditionally used to generate equally spaced and uniformly spread Pareto Frontiers for multi-objective optimization programming (MOP). This method tends to fail, however, when correlated objective functions must be optimized using Robust Parameter Designs (RPD). In such multi-objective optimization programming, there can be reached impractical optima and n...

Multiobjective Programming (MOP) has become famous among many researchers due to more practical and realistic applications. A lot of methods have been proposed especially during the past four decades. In this paper, we develop a new algorithm based on a new approach to solve MOP by starting from a utopian point, which is usually infeasible, and moving towards the feasible region via stepwise mo...