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Answers for “局部搜索优化的过程是什么,其主要限制是什么?”

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Simulated Annealing helps avoid getting stuck in a local minimum by probabilistically accepting worse solutions, especially in the early stages of the search. This acceptance is controlled by a parameter called 'temperature', which starts high and gradually decreases, allowing the algorithm to explore the solution space more broadly before converging.

Conditions: Requires an initial solution and a high initial temperature.; Uses a cooling schedule to gradually decrease the temperature.; Employs an acceptance criterion to decide whether to accept a worse solution based on the current temperature.

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A 2-Opt swap improves a route by selecting two edges in the current route, removing them, and reconnecting the four endpoints in a different way to form a new, valid cycle. This operation is particularly effective at eliminating self-intersections in a route, thereby reducing the total distance.

Conditions: Requires an existing valid TSP route.; Involves selecting two distinct edges.; The reconnection must produce a single valid cycle.