Iterated Maximum Large Neighborhood Search for the Traveling Salesman Problem with Time Windows and its Time-dependent Version

This article introduces a new algorithm for finding feasible or makespan-optimal solutions of Traveling Salesman Problems with Time Windows (TSPTWs) and Time-Dependent TSPTWs (TDTSPTWs). The starts from sequence visits the customers involved in problem, uses destroy repair operations to iteratively improve this sequence, applies perturbations diversify search. For phase, are removed current as long parameter called insertion-width is not too high. reinserted best based on dynamic programming procedure whose complexity only linear number customers. perturbation some randomly shifted visits. obtained Iterated Maximum Large Neighborhood Search (ImaxLNS). On seven standard TSPTW benchmarks, it returns best-known solution each instance less than one second average. two TDTSPTW benchmarks related urban logistics, provides solutions. benchmark Earth observing satellites, solves most instances second.