Network reconfiguration is a nonlinear optimization procedure which calculates a radial structure to optimize the power losses and improve the network reliability index while meeting practical constraints. In this paper, a multi-objective framework is proposed for optimal network reconfiguration with the objective functions of minimization of power losses and improvement of reliability index. T...

Heuristic techniques are optimization methods that inspired by nature. Although there many heuristics in the literature, a new heuristic technique is presented researchers every day observing nature-based or living behaviors In this study, human behavior proposed. order to prove validity of method called Search and Rescue Optimization Algorithm (AKOA), applied find global minimums function test...

Traditional optimization techniques such as Dynamic Programming(DP), Linear Programming(LP), and MixedInteger Programming(MIP) have been used to solve complex optimization problems in many diverse fields. Shortcomings of these classical techniques and the rapid development of affordable, powerful computing technology have led to the creation of new classes of heuristic-based optimizing techniqu...

Wireless Sensor Networks are the new generation of networks that typically are formed great numbers of nodes and the communications of these nodes are done as Wireless. The main goal of these networks is collecting data from neighboring environment of network sensors. Since the sensor nodes are battery operated and there is no possibility of charging or replacing the batteries, the lifetime of ...

An emerging, yet extremely important topic in simulation application and research is simulation optimization. Emphasis in the literature, in professional conferences, and particularly in commercial software packages underscore the importance of simulation optimization. We address this topic in a more general, model optimization venue. In particular we describe the use of a genetic algorithm in ...

as the science of mechanics has been improved in recent years, different standards have been created in designing structures such as pressure vessels. most of these standards have been developed by means of experience and examination. today, most of researches, proceed the numerical analysis of the different elements of the pressure vessels and somehow they have put some questions on the previo...

Structural optimization with frequency constraints is a challenging class of optimization problems characterized by highly non-linear and non-convex search spaces. When using a meta-heuristic algorithm to solve a problem of this kind, exploration/exploitation balance is a key feature to control the performance of the algorithm. An excessively exploitative algorithm might focus on certain areas ...

This study considers instant decision-making needs of the automobile manufactures for resequencing vehicles before final assembly (FA). We propose a rule-based two-stage stochastic model to determine the number of spare vehicles that should be kept in the pre-assembly buffer to restore the altered sequence due to paint defects and upstream department constraints. First stage of the model decide...

The performance of heuristic algorithms for combinatorial optimization is often sensitive to problem instances. In extreme cases, a specialized heuristic algorithm may perform exceptionally well on a particular set of instances while fail to produce acceptable solutions on others. Such a problem-sensitive nature is most evident in algorithms for combinatorial optimization problems such as job s...

 To use services transparently in a distributed environment, the Utility Grids develop a cyber-infrastructure. The parameters of the Quality of Service such as the allocation-cost and makespan have to be dealt with in order to schedule workflow application tasks in the Utility Grids. Optimization of both target parameters above is a challenge in a distributed environment and may conflict one an...