Metaheuristic Optimization for Vehicle Routing Problem with Time Windows (VRPTW)

Abstract

The problem of determining vehicle routes in logistics has a role Which on pIt isnting bagi company to reduce transportation costs and late fees. Time window constraints are very common in current distribution processes. This research focuses on optimizing fuel costs and penalties. In this study the authors used the Vehicle Routing Problem with Time Windows (VRPTW). VRPTW is one of the most tackled transportation problems in real world situations. Artificial Bee Colony Algorithm (ABC) and Camel Algorithm (CA) will be used in the research. Study This is Focused on optimizing fuel costs and penalties. Furthermore, the two algorithms will be compared which of the two algorithms is the most optimal for solving the route determination problem in VRPTW. Numerical testing will be carried out for the proposed algorithm, as well as conducting experiments on several parameters to determine the effect of parameters for fuel costs and penalties.

Combining participatory mapping and route optimization algorithms to inform the delivery of community health interventions at the last mile

“…We used the Google OR-Tools optimization VRPTW algorithm [24] to optimize CHW routes and home visits in each of the community health catchments (i.e. fokontany).…”

“…We implemented the default VRPTW algorithm developed by Google in Python 3.10 [24], using the reticulate package [29] for implementation with R software, version 4.3. The VRPTW algorithm uses four parameters: a travel time matrix (including the visit time per building), the departure and arrival locations, the time window for visits, and the number of CHWs [24]. The travel time matrix is a matrix of paired travel times between each and all destinations to be visited within a CHW catchment.…”