Bi-Attempted Base Optimization Algorithm on Optimization of Hydrosystems

Burhan Yildiz (), Mehtap Kose Ulukok () and Vali Bashiry ()
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Burhan Yildiz: Mugla Sitki Kocman University
Mehtap Kose Ulukok: Cyprus Science University
Vali Bashiry: Cyprus International University

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2023, vol. 37, issue 9, No 12, 3585-3597

Abstract: Abstract This study aims to search for optimum design parameters for a slurry pipeline problem and optimum operation parameters for a multi-reservoir scheduling problem by using Bi-Attempted Base Optimization Algorithm (ABaOA), which has been recently developed as a numerical bidirectional search algorithm. The slurry pipeline problem is a constrained non-linear cost minimization problem with constraints on facility capacities. It has two separate cost terms that behave differently with changes in decision variables. The problem includes several decision variables in addition to the fact that the objective function is highly non-linear. On the other hand, the multi-reservoir problem is a well-known problem in Hydraulics that aims to maximize benefit by optimizing the releases of each reservoir. The problem has a known global optimum, which is used to test the abilities of the ABaOA. The ABaOA is developed from Base Optimization Algorithm (BaOA) by transforming its operators with the aim to diversify the search paths to reach the global optimum. Its applications in hydrosystems show that it converges to the optimum solutions in reasonable times. The results from the first application are compared to the ones obtained from Genetic Algorithms (GA) application. It is observed that ABaOA outperformed GA in terms of speed of convergence and finding a better alternative solution. The ABaOA reaches the global optimum in the second application. In addition, alternatives with better benefit functions, including some penalties have been determined.

Keywords: Numerical optimization; Evolutionary algorithms; Multimodal functions; Slurry pipelines; Reservoir optimization; Hydraulics (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11269-023-03517-w

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