Local Search
A heuristic optimization method that iteratively searches the neighborhood of the current solution for better solutions. It is fast and suited to large-scale problems, but generally yields only approximately optimal solutions.
Timeline (last 90 days)
Hard constraints in local search are non-negotiable Boolean conditions (such as "open now" and "wheelchair accessible"), and if any condition is not satisfied the recommendation is deemed invalid; preferences are trade-off soft conditions (such as "quiet environment" and "high rating") and are usually handled by scoring or ranking.
Local search is fast and suitable for quickly obtaining feasible solutions in large-scale scenarios; HiGHS, as an exact solver, can give better or even optimal solutions on smaller-scale problems, but at higher computational cost.
All Facts (2)
Hard constraints in local search are non-negotiable Boolean conditions (such as "open now" and "wheelchair accessible"), and if any condition is not satisfied the recommendation is deemed invalid; preferences are trade-off soft conditions (such as "quiet environment" and "high rating") and are usually handled by scoring or ranking.
50%UnverifiedLocal search is fast and suitable for quickly obtaining feasible solutions in large-scale scenarios; HiGHS, as an exact solver, can give better or even optimal solutions on smaller-scale problems, but at higher computational cost.
50%