Metaheuristic Optimization

Researchers have developed alternative methodologies to deal with integer problems which are capable of finding very good solutions but they cannot guarantee for these solutions to be optimal. The solution procedures based on these methodologies are designed to search for improved solutions, however, at some point they give up. They return the best solution that they find which may be optimal but there is no guarantee of that. These methodologies are known as Metaheuristics, and the solutions that they find are known as heuristic solutions. Metaheuristics provide great flexibility. The modelling of the problem is not limited to linear functions. Example: Market basket analysis (a technique to generate practical rules that the store can apply in order to maximize its cross-selling opportunities. Objective: To establish rules that state if x is purchased, then y is also likely to be purchased. To measure the strength of the relationship between two items, market basket analysis uses Lift Ratio. If we have items x and y then the Lift Ratio tells us how much more likely it is for item y to be purchased given that item x has been purchased. For example, a Lift Ratio of 2 tells us that the moment x is purchased then the probability that y is also purchased doubles. Eg. Grocery stores – produce, dairy, meat, soft drinks, frozen food, brad and cookies Excel model: