Abstract
<div class="Section1"><p>In this paper a population-based meta-heuristic algorithm for optimization problems in a continous space is presented.The algorithm,here called cheapest shop seeker is modeled after a group of shoppers seeking to identify the cheapest shop (among many available) for shopping. The algorithm was tested on many benchmark functions with the result compared with those from some other methods. The algorithm appears to have a better success rate of hitting the global optimum point of a function and of the rate of convergence (in terms of the number of iterations required to reach the optimum value) for some functions in spite of its simplicity.</p></div>
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