Читать книгу Optimization and Machine Learning - Patrick Siarry - Страница 18

For the 2L-CVRP with time windows (2L-CVRPTW), a time window is assigned to each customer during which the customer demand is met. Attanasio et al. (2007) consider a variant of the 2L-CVRP where each shipment must take place within a multi-day time window (TW). They propose a cutting plane framework in which a simplified integer linear program (ILP) is solved. Items are allowed to be rotated and sequence-based loading is assumed.

Khebbache-Hadji et al. (2013) consider the weight limit of the vehicles as an additional constraint. The authors propose a memetic algorithm (MA) for both the routing and packing problems. Sbai et al. (2017) use a new heuristic based on an adaptive GA to solve the 2L-CVRP and designed an adaptive least wasted first (ALWF) heuristic to check the feasibility of the loading problem. Sbai et al. (2017) present an adaptive GA for solving the 2L-CVRP with time windows; the results improved the quality of the proposed solutions. Guimarans et al. (2018) propose a hybrid simheuristic algorithm to solve a version of the 2L-CVRP with stochastic travel times.

Song et al. (2019) consider the multi-objective VRP with loading and time window constraints, presented as a mixed integer linear programming (MILP) model. A generalized variable neighborhood search (GVNS) algorithm is designed to solve the MILP.