A simheuristic for routing electric vehicles with limited driving ranges and stochastic travel times

Green transportation is becoming relevant in the context of smart cities, where the use of electric vehicles represents a promising strategy to support sustainability policies. However the use of electric vehicles shows some drawbacks as well, such as their limited driving-range capacity. This paper analyses a realistic vehicle routing problem in which both driving-range constraints and stochastic travel times are considered. Thus, the main goal is to minimize the expected time-based cost required to complete the freight distribution plan. In order to design reliable Routing plans, a simheuristic algorithm is proposed. It combines Monte Carlo simulation with a multi-start metaheuristic, which also employs biased-randomization techniques. By including simulation, simheuristics extend the capabilities of metaheuristics to deal with stochastic problems. A series of computational experiments are performed to test our solving approach as well as to analyse the effect of uncertainty on the routing plans.Peer Reviewe

Multi-trip pickup and delivery problem, with split loads, profits and multiple time windows to model a real case problem in the constructionindustry

International audienceThis paper presents the first optimization study of multi-site transportation in the construction industry, whichallows mutualizing building material delivery and construction waste removal. This study is inspired by a real-worldproblem encountered in the framework of the French R&D project DILC, in which a pooling platformmust centralize the delivery of building materials to the construction sites and the pickup of their waste, usinga limited and heterogeneous fleet that are allowed to perform multiple trips, under time and capacity limitationconstraints. The problem under study, called the Multi-Trip Pickup and Delivery Problem, with Split loads,Profits and Multiple TimeWindows is a new extension of the vehicle routing problem with pickup and delivery,that considers new realistic constraints specific to the construction industry such as each construction site mayhave a priority on its delivery request or its pickup request or both, with a higher priority level for deliveryrequest, and each construction site may have several time windows. To solve this problem, we propose newinsertion criteria that takes into consideration several aspects of our problem, which we have embedded in aconstruction heuristic. Experiments performed on new real instances have shown the efficiency of our method

Thirty years of heterogeneous vehicle routing

It has been around thirty years since the heterogeneous vehicle routing problem was introduced, and significant progress has since been made on this problem and its variants. The aim of this survey paper is to classify and review the literature on heterogeneous vehicle routing problems. The paper also presents a comparative analysis of the metaheuristic algorithms that have been proposed for these problems

A Survey On Multi Trip Vehicle Routing Problem

The vehicle routing problem (VRP) and its variants are well known and greatly explored in the transportation literature. The vehicle routing problem can be considered as the scheduling of vehicles (trucks) to a set of customers under various side constraints. In most studies, a fundamental assumption is that a vehicle dispatched for service finishes its duty in that scheduling period after it returns back to the depot. Clearly, in many cases this assumption may not hold. Thus, in the last decade some studies appeared in the literature where this basic assumption is relaxed, and it is allowed for a vehicle to make multiple trips per period. We consider this new variant of the VRP an important one with direct practical impact. In this survey, we define the vehicle routing problem with multiple trips, define the current state-of-the-art, and report existing results from the current literature

A dynamic ridesharing dispatch and idle vehicle repositioning strategy with integrated transit transfers

We propose a ridesharing strategy with integrated transit in which a private on-demand mobility service operator may drop off a passenger directly door-to-door, commit to dropping them at a transit station or picking up from a transit station, or to both pickup and drop off at two different stations with different vehicles. We study the effectiveness of online solution algorithms for this proposed strategy. Queueing-theoretic vehicle dispatch and idle vehicle relocation algorithms are customized for the problem. Several experiments are conducted first with a synthetic instance to design and test the effectiveness of this integrated solution method, the influence of different model parameters, and measure the benefit of such cooperation. Results suggest that rideshare vehicle travel time can drop by 40-60% consistently while passenger journey times can be reduced by 50-60% when demand is high. A case study of Long Island commuters to New York City (NYC) suggests having the proposed operating strategy can substantially cut user journey times and operating costs by up to 54% and 60% each for a range of 10-30 taxis initiated per zone. This result shows that there are settings where such service is highly warranted

Optimization of LPG Distribution Route Using Variable Neighborhood Tabu Search Algorithm

PT. Galaxi Energi Pratama (GEP) is one of the biggest distributors of subsidized LPG in Malang Raya area. Currently the route planning is not done very well, which results in a high fuel cost. With the company's main business process being distribution, the planning needs to be improved to maximize the profit. The problem in PT. GEP is classified as the Heterogeneous Vehicle Routing Problem with Multiple Trips (HVRPM). This problem is classified as NP-Hard and requires high computational effort to obtain a good solution so metaheuristic method is preferred. In this research, variable neighborhood tabu search (VNTS) algorithm is developed to solve the HVRPM and implemented to minimize the fuel cost of PT. GEP. The developed algorithm is implemented in the six instances collected from the case study. The generated trips produce a total savings of Rp 150,876 for one operational week, or roughly 18% of the initial cost. The computation time of the algorithm is evaluated by comparing with Simulated Annealing using a problem with the same size. VNTS has a lower average time and is expected to perform competitively when a standardized dataset is used for comparison. The solution quality of the algorithm is then compared with branch-and-bound method. VNTS is able to find one global optimal solution out of the six instances and overall, it performs better than branch-and-bound

Waste Collection Vehicle Routing Problem Model with Multiple Trips, Time Windows, Split Delivery, Heterogeneous Fleet and Intermediate Facility

Waste Collection Vehicle Routing Problem (WCVRP) is one of the developments of a Vehicle Routing Problem, which can solve the route determination of transporting waste. This study aims to develop a model from WCVRP by adding characteristics such as split delivery, multiple trips, time windows, heterogeneous fleet, and intermediate facilities alongside an objective function to minimize costs and travel distance. Our model determines the route for transporting waste especially in Cakung District, East Jakarta. The additional characteristics are obtained by analyzing the characteristics of waste transportation in the area. The models are tested using dummy data to analyze the required computational time and route suitability. The models contribute to determining the route of transporting waste afterward. The WCVRP model has been successfully developed, conducted the numerical testing, and implemented with the actual characteristics such as split delivery, multiple trips, time windows, heterogeneous fleets, and intermediate facilities. The output has reached the global optimal for both dummy and real data

MODEL OF VEHICLE ROUTING PROBLEM WITH SPLIT DELIVERY, MULTI TRIPS, MULTI PRODUCTS AND COMPARTMENTS FOR DETERMINING FUEL DISTRIBUTION ROUTES

The industrial development in Indonesia encourages companies to have high sensitivity in competing to meet consumer demands promptly by considering minimum distribution costs. One of the factors that can affect distribution costs is route determination. Determining the distribution route is the Vehicle Routing Problem (VRP). The purpose of VRP is to arrange the order of distribution routes to produce a minimum total distance. This study aims to determine the fuel distribution route at TBBM Rewulu in one delivery period to obtain the optimal distribution route and minimize the vehicle mileage. Delivery is carried out using three types of tanker trucks with heterogeneous capacities. This study uses a mathematical model of Mixed Integer Linear Programming (MILP) by considering split delivery, multi trips, multi-products, and compartments.The branch and bound method in the LINGO solver has been used to solve this problem. This model was tested on a simple case using data of 8 customers with different distances and demand shipped by truck. The results obtained indicate that no boundaries are violated, and all consumers are served. The mathematical model built is still general, so it can solve similar cases. A model can be developed for further research by adding VRP variants such as time windows and adding the product types to represent the entire existing system

Algorithm design for the fleet sizing problem in grocery retail distribution

From the classical Vehicle Routing Problem (VRP) and other extensions as well, our research will focus on constraints within grocery retail distribution. Usually they are tackled in the literature as VRP with multiple compartments and multiple trip VRP. Furthermore, we will cope with time windows and other extensions. In addition, our problem will be stated and a solution proposal will be sketched, both considering heuristic and exact approaches