The objective of this project is to optimally schedule pumps to ensure that while in operation the operational efficiency is high but at the same time the cost of running the pump is kept on the minimum.

This project dwells on pumping systems especially water supply pumping systems. Society keeps growing each day and this, therefore, means that demand for basic commodities is on the increase. Water is a basic need for human life and is of great demand. To meet the given demands water supply systems must be expanded in relation to demand. Pump scheduling optimization has therefore become necessary. The main aim of pump scheduling is to schedule the operation of a given number of pumps in such a way that system constrains and boundary conditions are satisfied while operation cost is minimized. Most important costs associated with pump operations are electrical and maintenance cost. This adds up to the total cost of running the pump system thus making it costly altogether. Ways have to be found on how best these problems have to be overcome without compromise the operation results at the end. Various techniques are applied, some manually some automated. All this cuts down to what is the most suitable approach.

To efficiently schedule pumps different approaches have been used before. These include linear programming, non linear programming, multi objective approach and genetic algorithm optimization [5]. However, in this project we approach the problem using particle swarm optimization. This approach will be expounded further in the following chapters. The report approaches the issue by considering water supply systems which are the most common systems that heavily rely on pumping systems.

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