Cost optimization of rectangular RC footing using GA and UPSO

Cost Effective Design of RC Building Frame Employing Unified Particle Swarm Optimization

“…In that way accuracy of the results can be improved further. For deflection check in beam [7] Simplex and Lagrangian optimization method Chakrabarty [8] Geometric programming Coello et al [9], Rajeev and Krishnamoorthy [10], Chaudhuri and Maity [20] Genetic algorithm (GA) Dole et al [11] polynomial optimization technique De Medeiros et al [12] Simulated annealing (SA) Nigdeli and Bekdaş [13] random search technique (RST) Uz et al [14], Kaveh and Behnam [21] charged system search (CSS) Preethi and Arulraj [16] sequential quadratic programming (SQP) Bekdaş and Niğdeli [17] Teaching-learning-based-optimization (TLBO) Bekdaş and Nigdel [22] Harmony search (HS) Aga and Adam [23] Artificial neural network (ANN) Gharehbaghi and Khatibinia [24] intelligent regression model (IRM) combined with Particle swarm optimization (PSO) Esfandiary et al [25,29] decision-making Particle Swarm Optimization (DMPSO) Kulkarni and Bhusare [26] Response Surface Method (RSM) Tapao and Cheerarot [28] Artificial bee colony (ABC) RazmaraShooli et al [30] GA-PSO algorithm Chaudhuri and Maity [20] Unified particle swarm optimization (UPSO)…”

“…Thus, the method developed in the present studyaims towards alleviate these shortcomings. Also Unified Particle Swarm Optimization has not been used asa cost optimization method for multistory building design in the previous studies, although it has been used very effectively in cost optimization of RC foundation [20], damage detection problems [33][34][35][36][37][38], magnetoencephalography problem [39] etc. Hence, UPSO have been found to the appropriate optimization method for multistory building design and cost optimization.…”

“…Cost optimum design of T-beams [15]andCost optimum design RC columns [7,16,17] also have been attempted. Apart from beam and column optimization, design of reinforced concrete (RC) flat slabs have also been optimized by Aldwaik and Adeli [18] using Neural dynamic model for Adeli and Park (NDAP) [19], Design optimization of RC foundation has been performed by Chaudhuri and Maity [20].…”

“…Besides these individual structural components researchers have also tried to optimize the beam-column frames in terms of weight [21], in terms of cost [22][23][24][25][26][27][28][29]. All these studies regarding design optimization of RC building components or frames are conformed to the guidelines decided by the various standards of different countries such as Indian standard (IS 456) [7,11,20,26], American standard (ACI 318, ASCE7) [13,17, 21-25, 28, 29], European standard (Eurocode 2) [15,27]and Australian standard (AS 3600) [14], Brazilian standard (NBR 6118) [12]. Apart from these, RazmaraShooli et al [30] have proposed a GA-PSO based algorithm for performance-based design optimization of a special moment-resisting frames based on guidelines provided by American standards (ATC-40, FEMA 356, ASCE-7 and ASCE-41).In these literatures the researchers used geometry of beam, column, amount of reinforcement, cost of material and shuttering as their optimization variable.In the problems regarding optimized design of RC components, optimizing the distribution of reinforcement are also an important issue [31,32].…”

Optimum Design of RC Footings with Genetic Algorithms According to ACI 318-19

“…In Luévanos-Rojas et al [7,8], optimization was applied to the design of concrete footings using a soil pressure model that requires the computation of several integrals in the constraint functions. Chaudhuri et al [9] used GA and unified particle swarm optimization (UPSO) strategies for the design of footings according to IS 456 2000, showing that both implementations produce noticeable better solutions than some popular structural design commercial packages in terms of material cost. Khajehzadeh et al [10] presents an interesting multi-objective optimization (MOO) approach for the design of spread footings, where one of the objective functions quantifies the total amount of CO 2 emissions resulting from the material usage.…”