Abstract
A new promising metaheuristic algorithm, named search economics (SE), is described in this chapter. The unique characteristics of SE are that it first divides the solution space into a set of subspaces (regions) and then uses the expected value of a region to replace the objective or fitness value of a solution to determine later search directions. The expected value is inspired by the return on investment (ROI), which is composed of the following pieces of information: (1) status of investment, (2) potential of investment, and (3) the landscape of each region. The major operators of SE—namely, resource arrangement, vision search, and marketing research—are also described. SE is applied to the one-max problem and compared with other metaheuristic algorithms to show the possibilities and potential of SE.
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