| Summary: | 碩士 === 國立臺灣科技大學 === 營建工程系 === 102 === Construction Engineering Optimization problem is a complex optimization problem and also has many type of problem such as Structural Optimization, Tower Crane Layout Optimization, etc. Structural optimization problem is an optimization problem with large number of variables and constraint that prevent engineer to get the optimum design in reasonable time. Meanwhile, Tower Crane Layout (TCL) problem is a complex and uneasy optimization which involves arranging and determining the tower crane locations and also the locations of supply points. To solve the structural optimization and TCL problem, metaheuristic approach was applied. This study proposes a new hybrid metaheuristic algorithm named Evolutionary Big Bang – Big Crunch (EBB-BC). EBB-BC is a hybrid algorithm from Big Bang - Big Crunch algorithm, Neighborhood Search and Differential Evolution algorithm using collaborative combination hybridization concept. This study compares the performance of EBB-BC with other well-known algorithm using some unconstrained benchmark functions problems. Moreover, this study compares EBB-BC with other well-known metaheuristic algorithm in solving structural optimization problem and TCL problem. The results show the excellence performance of EBB-BC where EBB-BC outperforms all other algorithms tested both in solving benchmark functions, structural optimization and TCL problem.
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