Structural Design Optimization of Flat Slab Hospital Buildings Using Genetic Algorithms

Abstract

The construction costs of hospital buildings are relatively high due to the need to fulfill their complex functions and avoid mishaps. In this context, this study aims to minimize the total construction costs of hospitals while still satisfying the special architectural, practical, and structural requirements specified by design codes. To this end, 48 design alternatives with two floor systems (flat slabs with and without drop panels), three column spacings, and eight concrete grades were optimized using genetic algorithms provided by Palisade Evolver. The objective function included the materials and labor costs per square meter of the floor plan. The decision variables involved the concrete dimensions and steel bars of floors and columns. The hospital buildings were subjected to gravity, earthquake, and wind loads to thoroughly examine the realistic loading conditions. The design was performed in accordance with the Egyptian code for the design and construction of concrete structures and the Egyptian guidelines for hospitals and healthcare facilities. The results revealed that using low-strength concrete, and flat slabs without drop panels could achieve the best design. The slab thickness had a governing impact on the total cost of both floor systems.