a shortest path problem is a practical issue in networks for real-world situations. this paper addresses the fuzzy shortest path (fsp) problem to obtain the best fuzzy path among fuzzy paths sets. for this purpose, a new efficient algorithm is introduced based on a new definition of ideal fuzzy sets (ifss) in order to determine the fuzzy shortest path. moreover, this algorithm is developed for ...

The human has always been to find the best in all things. This Perfectionism has led to the creation of optimization methods. The goal of optimization is to determine the variables and find the best acceptable answer Due to the limitations of the problem, So that the objective function is minimum or maximum. One of the ways inaccurate optimization is meta-heuristics so that Inspired by nature, ...

In this paper, an intelligent-gradient based algorithm is proposed to solve time optimal bang-bang control problem. The proposed algorithm is a combination of an intelligent algorithm called improved particle swarm optimization algorithm (IPSO) in the first stage of optimization process together with a gradient-based algorithm called successive quadratic programming method (SQP) in the second s...

proper scheduling of tasks leads to optimum using of time and resources, inorder to obtaining best result. one of the most important and complicatedscheduling problems is open shop scheduling problem. there are n jobs in openshop scheduling problem which should be processed by m machines. purpose ofscheduling open shop problem is attaining to a suitable order of processing jobs byspecified mach...

in this paper, we present a new path-following interior-point algorithm for -horizontal linear complementarity problems (hlcps). the algorithm uses only full-newton steps which has the advantage that no line searchs are needed. moreover, we obtain the currently best known iteration bound for the algorithm with small-update method, namely, , which is as good as the linear analogue.

This paper introduces the optimization algorithm to improve search rate in urban path routing problems using viral infection and local search in urban environment. This algorithm operates based on two different approaches including wavelet transform and genetic algorithm. The variables proposed by driver such as degree of difficulty and difficulty traffic are of the essence in this technique. W...

recently different approaches have been developed in the field of sensor fault diagnostics based on auto-associative neural network (aann). in this paper we present a novel algorithm called self reconstructing auto-associative neural network (s-aann) which is able to detect and isolate single faulty sensor via reconstruction. we have also extended the algorithm to be applicable in multiple faul...