Nature inspired solutions for real time dynamic problems

Abstract

Real time (Dynamic) optimization problems which are a category of combinatorial newlineoptimization problems are considered as a class of common optimization problems in newlinewhich the values of decision variables are very vital constraints. Real time (Dynamic) newlineoptimization problems are commonly encountered in the real world [1]. Because of their newlineconstraints, an enumeration method may be used to find the optimal solutions for these newlineproblems. Here solution search space of these optimization problems normally grow newlineexponentially based on the size problems and can be also classified as NP-hard problems newline[2]. So, exact optimization methods like branch and bound may fail to obtain optimal newlinesolutions to real time (Dynamic) problems which are in large size within acceptable newlinecomputation time. Sometimes heuristic methods also face difficulties in finding high newlinequality solutions. Recently, some algorithms, particularly nature inspired algorithms have newlineapplied to certain real time (Dynamic) optimization problems and best results have newlineobtained in acceptable time [3][4]. The results obtained give an idea about the newlinepotentiality of such nature inspired approaches in solving other types of real time newline(Dynamic) optimization problems. newline