This paper focuses on a metamodel-based design optimization algorithm. The intention is to improve its computational cost and convergence rate. Metamodel-based optimization method introduced here, provides the necessary means to reduce the computational cost and convergence rate of the optimization through a surrogate. This algorithm is a combination of a high quality approximation technique called Inverse Distance Weighting and a metaheuristic algorithm called Harmony Search. The outcome is then polished by a semi-tabu search algorithm. This algorithm adopts a filtering system and determines solution vectors where exact simulation should be applied. The performance of the algorithm is evaluated by standard truss design problems and there has been a significant decrease in the computational effort and improvement of convergence rate.

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Design process, due to its information-and innovation-intensive nature, is highly susceptible to change and thus, waste. This attracted the attention of lean design/construction professionals in the past few years. However, limited, if any, researches have addressed this issue from the human behavior perspective. This research proposes a method that exploits the potential of the Last Planner ® System (LPS) in design management. The main contribution of this paper is improving the applicability of the LPS to design processes by incorporating a gami ed pay-for-performance system into the normal practice of the LPS. It encourages motivating design engineers by granting them singlepoint, autonomous responsibility to perform their tasks. To this end, the proposed method shifts the focus of design managers away from predicting the work ow and chronologies of design tasks to motivate design engineers to eliminate non-value-adding works/time. To bolster the concept and examine the method, it was put into practice by construction design teams. Findings corroborate the e ciency of the method in eliminating the nonvalue-adding works from design processes. The ndings are of practical value to consulting rms, especially design team managers who seek to maximize innovation, competency, and quality outcome.