Discrete Event Simulation, Greedy Algorithm, Resource Optimization, Arena Simulation, Heuristic Algorithm, System Optimization


Architecture | Business | Engineering | Physical Sciences and Mathematics


Supermarkets worldwide are facing a service dilemma whether to increase or decrease their number of counters used at checkouts. A higher number of checkouts will undoubtedly reduce waiting time at checkout, a factor in improving customer satisfaction and service quality but this will come at a cost to the Supermarket. The work conducted in this paper will therefore focus on this tradeoff between improving the customer shopping experience versus the Supermarket Cost and profitability margins. It will do so by using an optimization algorithm that can help find the optimum number of checkouts and utilization of staff resources. The optimization algorithm uses discrete event simulation approach that applies arena integrated with Greedy algorithm, using real-life data The aim of this integration is to combine the strength of the simulation that optimize large set of feasible solutions, with the advantage of the greedy algorithm to reduce the design space of feature inputs, which would facilitate optimizing the process in the shortest time possible. The developed integrated greedy algorithm has proved successful in optimizing the staff resource efficiency as well as achieving the optimum number of checkouts.





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