Tabu search keeps a short-term memory of recently reversed moves or visited attributes and prohibits them temporarily, reducing cycling in local search. It can select the best admissible neighbor even when that neighbor worsens the objective; an aspiration rule permits a tabu move when it improves the best known solution. For allocations, transfers and exchanges maintain feasibility and recent reverse transfers can be tabu.
Tabu search is an advanced metaheuristic optimization algorithm that is used for solving combinatorial and continuous optimization problems. It is designed to navigate the solution space efficiently by avoiding local optima through the use of memory structures. Here are the key features and components that characterize Tabu search: 1. **Memory Structure**: Tabu search uses a memory structure to keep track of previously visited solutions, known as "tabu" list.
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