An optimization model to minimize the cost of designing water distribution network is presented in this study. The model was formulated to reduce the cost coefficient in a plumbing system. A new hybrid method of optimization was constructed by combining the search abilities of Jaya-based algorithm and pollination intelligence algorithm, and was used to solve the designed model. The model was implemented by obtaining geometrical information of a water distribution network layout stationed at Gaa Odota, Ilorin, Kwara State, Nigeria. Result obtained from the model showed a significant reduction in the cost coefficient compared to that of the study area.
In this paper, a new metaheuristic algorithm named refined heuristic intelligence swarm (RHIS) algorithm is developed from an existing particle swarm optimization (PSO) algorithm by introducing a disturbing term to the velocity of PSO and modifying the inertia weight, in which the comparison between the two algorithms is also addressed.
Cuckoo Search (CS) algorithm is a meta-heuristic technique that displays several merits. For example, it is easier to apply and less tuning parameters also, it is suitable for solving optimization problems. However, easily fall into local optimum has been established and has a slow convergence rate as a result of the cuckoo search parameters being kept constant. Therefore to handle this issue, an Enhanced Cuckoo Intelligence Search (ECIS) algorithm was developed which is an upgraded CS algorithm. The efficiency of ECIS was tested by some benchmark constrained optimization test functions and it was shown that ECIS gives a better optimal value than CS.
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