Framework For A Multi-Level Evolutionary Algorithm For Construction Optimization


Construction; Evolutionary algorithms; Optimization


In large-scale non-linear construction optimization problems, the capability of an algorithm to find the optimal solution is usually limited by the inability to evaluate the effect of change in the value of each decision variable on the overall outcome of the objective function. Current optimization algorithms evaluate the quality of generated solutions based only on the value of fitness/objective function. As such, these algorithms are limited in their ability to robustly reach optimal solutions. This paper presents a framework for an innovative evolutionary algorithm that mimics the behavior of electrons moving through electric circuit branches with the least resistance. In the proposed algorithm, solutions are evaluated on two levels: a global level against the objective function; and a local level by evaluating the potential of the generated value for each decision variable. This paper presents (1) the philosophy behind this work; (2) the concept adopted in developing the algorithm; and (3) the basic steps of the algorithm. The new algorithm is expected to enhance the optimization of complex large-scale optimization problems. © ECMS.

Publication Date


Publication Title

Proceedings - 23rd European Conference on Modelling and Simulation, ECMS 2009

Number of Pages


Document Type

Article; Proceedings Paper

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Socpus ID

84857766494 (Scopus)

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