When facing certain problems in science, engineering or technology, it is not enough to find a solution, but essential seek and the best possible solution through optimization. In many cases exact optimization procedures are applicable due great computational complexity of problems. As an alternative optimization, there approximate algorithms, whose purpose reduce by pruning some areas problem ...

This chapter proposes new heuristic algorithms to solve grid scheduling problem. Two heuristic algorithms, based on Ant Colony Optimization and Particle Swarm Optimization are proposed. The optimization criteria, namely, flowtime and makespan are used to measure the quality of grid scheduling algorithm. Using the simulated benchmark instances, the results of different algorithms are analyzed an...

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 then re...

The Charged System Search (CSS) is combined to chaos to solve mathematical global optimization problems. The CSS is a recently developed meta-heuristic optimization technique inspired by the governing laws of physics and mechanics. The present study introduces chaos into the CSS in order to increase its global search mobility for a better global optimization. Nine chaos-based CSS (CCSS) methods...

Recently, many meta-heuristic algorithms are proposed for optimization of various problems. Some of them originally are presented for continuous optimization problems and some others are just applicable for discrete ones. In the literature, sizing optimization of truss structures is one of the discrete optimization problems which is solved by many meta-heuristic algorithms. In this paper, in or...

The integrated product mix-outsourcing optimization is a major problem in manufacturing enterprise. Generally, heuristic or meta-heuristic solution approaches are used to optimize such problems. Heuristic approaches for these problems include Theory of Constraints (TOC) and Standard Accounting. Sometimes heuristic approaches are inefficient especially in large problems and instead, in these cas...

Heuristic algorithms are able to optimize objective functions efficiently because they use intelligently the information about functions. Thus, utilization is critical performance of heuristics. However, concept has remained vague and abstract there no reliable metric reflect extent which function utilized by heuristic algorithms. In this paper, ratio (IUR) defined, quantity over acquired in se...

Given a heuristic estimate of the relative safety of a hybrid dynamical system trajectory, we transform the initial safety problem for dynamical systems into a global optimization problem. We introduce MLLO-IQ and MLLO-RIQ, two new information-based optimization algorithms. After demonstrating their strengths and weaknesses, we describe the class of problems for which diierent optimization meth...