An Adapted Version of the Water Wave Optimization Algorithm for the Capacitated Vehicle Routing Problem with Time Windows with Application to a Real Case Using Probe Data

Letizia Tebaldi,Teresa Murino,Eleonora Bottani

doi:10.3390/su12093666

Letizia Tebaldi, Teresa Murino + Show 1 more

Open Access

https://doi.org/10.3390/su12093666

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Abstract

Customers’ habits, as far as shipping requests are concerned, have changed in the last decade, due to the fast spread of e-commerce and business to consumer (B2C) systems, thus generating more and more vehicles on the road, traffic congestion and, consequently, more pollution. Trying to partially solve this problem, the operational research field dedicates part of its research to possible ways to optimize transports in terms of costs, travel times, full loads etc., with the aim of reducing inefficiencies and impacts on profit, planet and people, i.e., the well-known triple bottom line approach to sustainability, also thanks to new technologies able to instantly provide probe data, which can detail information as far as the vehicle behavior. In line with this, an adapted version of the metaheuristic water wave optimization algorithm is here presented and applied to the context of the capacitated vehicle routing problem with time windows. This latter one is a particular case of the vehicle routing problem, whose aim is to define the best route in terms of travel time for visiting a set of customers, given the vehicles capacity and time constraints in which some customers need to be visited. The algorithm is then tested on a real case study of an express courier operating in the South of Italy. A nearest neighbor heuristic is applied, as well, to the same set of data, to test the effectiveness and accuracy of the algorithm. Results show a better performance of the proposed metaheuristic, which could improve the journeys by reducing the travel time by up to 23.64%.

Highlights

There is no doubt that together with industry 4.0, big data, artificial intelligence, climate change and many others, sustainability is one of the keywords of the 21st century we are living
An adapted version of the metaheuristic water wave optimization algorithm is here presented and applied to the context of the capacitated vehicle routing problem with time windows. This latter one is a particular case of the vehicle routing problem, whose aim is to define the best route in terms of travel time for visiting a set of customers, given the vehicles capacity and time constraints in which some customers need to be visited
Results show a better performance of the proposed metaheuristic, which could improve the journeys by reducing the travel time by up to 23.64%

Summary

Introduction

There is no doubt that together with industry 4.0, big data, artificial intelligence, climate change and many others, sustainability is one of the keywords of the 21st century we are living . The CVRPTW can be seen as the realistic case of an express courier which has to deliver goods to a set of customers in a day and some customers, normally with a price increase, need to be visited in a specific time span This kind of problem has several implications in terms of the impacts generated during the transport activity, in all the three sustainability dimensions that are above-mentioned. As far as the solution algorithm is concerned, in literature, there is evidence of various strategies developed to solve the class of VRPs, including the CVRPTW itself; particular attention has been paid to the metaheuristic algorithms These latter represent a set of stochastic approaches that set off with a randomly generated population, which is subsequently updated by using a succession of different mathematical operations, primarily inspired by some activities of the natural law [12].

Background

The Adapted Water Wave Optimization to the CVRPTW

Findings

Conclusions