Diving heuristics are methods that progressively enlarge a partial solution up to its possible completion, thus ˇjump˘into a solution with no way back. While this is common to all constructive heuristics, diving ones are usually characterized by working on the mathematical formulation of the problem to solve. Some contributions of this type showed remarkably effective, and are included as standard components of general MIP solvers. This chapter reviews two well-known diving heuristics, namely Relaxation Induced Neighborhood Search (RINS) and Local Branching, and outlines a possible specification to the Generalized Assignment Problem.
Maniezzo, V., Boschetti, M.A., Stützle, T. (2021). Diving Heuristics. Cham : Springer [10.1007/978-3-030-70277-9_5].
Diving Heuristics
Maniezzo, Vittorio;Boschetti, Marco Antonio;
2021
Abstract
Diving heuristics are methods that progressively enlarge a partial solution up to its possible completion, thus ˇjump˘into a solution with no way back. While this is common to all constructive heuristics, diving ones are usually characterized by working on the mathematical formulation of the problem to solve. Some contributions of this type showed remarkably effective, and are included as standard components of general MIP solvers. This chapter reviews two well-known diving heuristics, namely Relaxation Induced Neighborhood Search (RINS) and Local Branching, and outlines a possible specification to the Generalized Assignment Problem.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
