Bilevel programming, a tool for modeling decentralized decision problems, consists of the objective of the leader at its first level and that of the follower at the second level. Bilevel programming has been proved to be an Np-hard problem. Numerous algorithms have been developed for solving bilevel programming problems. These algorithms lack the required efficiency for solving a real problem. ...

We introduced and discussed a second-ordered parametric dual model of complex multi-objective programming problem (P). Moreover, the authors constructed proved weak, strong strictly converse duality theorems by generalized Θ-bonvexity.

In this paper, three criteria scheduling problem of n jobs on a single machine is considered. Each these to be processed without interruption and becomes available for processing at time zero. The minimize objectives simultaneously, which are the completion time, maximum tardiness, earliness. Here, we develop fuzzy multi-objective linear programming (FMOLP) model solving in environment by using...

Humanitarian organizations pre-position relief items in pre-disaster and distribute them to the affected areas in post-disaster. Improper planning of emergency operations causes more deaths in post-disaster. In this paper, the problem of relief item pre-positioning and multi-period distribution planning is addressed considering lateral transhipment among distribution centres to improve the effi...

this paper presents a multi-objective linear programming model for disaster blood supply chain in some periods of time after disaster. this model assist to determine the quantity and location of facilities and also how to allocate blood to facilities. in this study, a three-level model is described, while blood is collected from temporary and permanent facilities and sent to blood center. blood...

Multi-objective De Novo linear programming (MODNLP) is problem for designing optimal system by reshaping the feasible set (Fiala [3] ). This paper deals with MODNLP having possibilistic objective functions coefficients. The problem is considered by inserting possibilistic data in the objective functions coefficients. The solution of the problem is defined and established under the using of effi...

A Real-Time Optimization (RTO) strategy incorporating the fuzzy sets theory is developed, where the problem constraints obtained from process considerations are treated in fuzzy environment. Furthermore, the objective function is penalized by a fuzzified form of the key process constraints. To enable using conventional optimization techniques, the resulting fuzzy optimization problem is the...