Edward A. Wasil

The vehicle routing problem : latest advances and new challenges

Overviews and Surveys.- Routing a Heterogeneous Fleet of Vehicles.- A Decade of Capacitated Arc Routing.- Inventory Routing.- The Period Vehicle Routing Problem and its Extensions.- The Split Delivery Vehicle Routing Problem: A Survey.- Challenges and Advances in A Priori Routing.- Metaheuristics for the Vehicle Routing Problem and Its Extensions: A Categorized Bibliography.- Parallel Solution Methods for Vehicle Routing Problems.- Recent Developments in Dynamic Vehicle Routing Systems.- New Directions in Modeling and Algorithms.- Online Vehicle Routing Problems: A Survey.- Modeling and Solving the Capacitated Vehicle Routing Problem on Trees.- Using a Genetic Algorithm to Solve the Generalized Orienteering Problem.- An Integer Linear Programming Local Search for Capacitated Vehicle Routing Problems.- Robust Branch-Cut-and-Price Algorithms for Vehicle Routing Problems.- Recent Models and Algorithms for One-to-One Pickup and Delivery Problems.- One-to-Many-to-One Single Vehicle Pickup and Delivery Problems.- Challenges and Opportunities in Attended Home Delivery.- Chvatal-Gomory Rank-1 Cuts Used in a Dantzig-Wolfe Decomposition of the Vehicle Routing Problem with Time Windows.- Vehicle Routing Problems with Inter-Tour Resource Constraints.- From Single-Objective to Multi-Objective Vehicle Routing Problems: Motivations, Case Studies, and Methods.- Practical Applications.- Vehicle Routing for Small Package Delivery and Pickup Services.- Advances in Meter Reading: Heuristic Solution of the Close Enough Traveling Salesman Problem over a Street Network.- Multiperiod Planning and Routing on a Rolling Horizon for Field Force Optimization Logistics.- Health Care Logistics, Emergency Preparedness, and Disaster Relief: New Challenges for Routing Problems with a Focus on the Austrian Situation.- Vehicle Routing Problems and Container Terminal Operations - An Update of Research.

The team orienteering problem

In the team orienteering problem, start and end points are specified along with other locations which have associated scores. Given a fixed amount of time for each of the M members of the team, the goal is to determine M paths from the start point to the end point through a subset of locations in order to maximize the total score. In this paper, a fast and effective heuristic is presented and tested on 353 problems ranging in size from 21 to 102 points. The computational results are presented in detail.

The Impact of Metaheuristics on Solving the Vehicle Routing Problem: Algorithms, Problem Sets, and Computational Results

In the standard, capacitated vehicle routing problem (VRP), a homogeneous fleet of vehicles services a set of customers from a single depot. Each vehicle has a fixed capacity that cannot be exceeded and each customer has a known demand that must be satisfied. Each customer must be serviced by exactly one visit of a single vehicle and each vehicle must leave and return to the depot. There may be route-length restrictions that limit the distance traveled by each vehicle. The objective is to generate a sequence of deliveries for each vehicle so that all customers are serviced and the total distance traveled by the fleet is minimized.

A fast and effective heuristic for the orienteering problem

Abstract In the orienteering problem, start and end points are specified along with other locations which have associated scores. Given a fixed amount of time, the goal is to determine a path from the start point to the end point through a subset of locations in order to maximize the total path score. In this paper, a fast and extremely effective heuristic is presented and tested on 67 problems taken from the literature and 40 new test problems. The computational results are presented in detail.

Very large-scale vehicle routing: new test problems, algorithms, and results

The standard vehicle routing problem was introduced in the OR/MS literature about 45 years ago. Since then, the vehicle routing problem has attracted an enormous amount of research attention. In the late 1990s, large vehicle routing problem instances with nearly 500 customers were generated and solved using metaheuristics. In this paper, we focus on very large vehicle routing problems. Our contributions are threefold. First, we present problem instances with as many as 1200 customers along with estimated solutions. Second, we introduce the variable-length neighbor list as a tool to reduce the number of unproductive computations. Third, we apply record-to-record travel with a variable-length neighbor list to 32 problem instances and obtain high-quality solutions, very quickly.

Using Experimental Design to Find Effective Parameter Settings for Heuristics

In this paper, we propose a procedure, based on statistical design of experiments and gradient descent, that finds effective settings for parameters found in heuristics. We develop our procedure using four experiments. We use our procedure and a small subset of problems to find parameter settings for two new vehicle routing heuristics. We then set the parameters of each heuristic and solve 19 capacity-constrained and 15 capacity-constrained and route-length-constrained vehicle routing problems ranging in size from 50 to 483 customers. We conclude that our procedure is an effective method that deserves serious consideration by both researchers and operations research practitioners.

The open vehicle routing problem: Algorithms, large-scale test problems, and computational results

In the open vehicle routing problem (OVRP), a vehicle does not return to the depot after servicing the last customer on a route. The description of this variant of the standard vehicle routing problem appeared in the literature over 20 years ago, but has just recently attracted the attention of practitioners and researchers. Today, the OVRP is encountered in practice in the home delivery of packages and newspapers. Contractors who are not employees of the delivery company use their own vehicles and do not return to the depot. In the last five years, tabu search, deterministic annealing, and large neighborhood search have been applied to the OVRP with some success. In this paper, we review OVRP algorithms, develop a variant of our record-to-record travel algorithm for the standard vehicle routing problem to handle open routes, and report computational results on test problems taken from the literature. Finally, we develop a set of eight large-scale problems that range in size from 200 to 480 nodes and report solutions generated by our record-to-record travel algorithm on this test set.

A record-to-record travel algorithm for solving the heterogeneous fleet vehicle routing problem

In the heterogeneous fleet vehicle routing problem (HVRP), several different types of vehicles can be used to service the customers. The types of vehicles differ with respect to capacity, fixed cost, and variable cost. We assume that the number of vehicles of each type is fixed and equal to a constant. We must decide how to make the best use of the fixed fleet of heterogeneous vehicles. In this paper, we review methods for solving the HVRP, develop a variant of our record-to-record travel algorithm for the standard vehicle routing problem that takes a heterogeneous fleet into account, and report computational results on eight benchmark problems. Finally, we generate a new set of five test problems that have 200-360 customers and solve each new problem using our record-to-record travel algorithm.

An improved heuristic for the period vehicle routing problem

In the period vehicle routing problem, each customer requires a certain number of deliveries per week. Given these frequency requirements, customers must be allocated to days. A vehicle routing problem is solved over each day. We have improved upon best-known solutions to problems from the literature using a new heuristic procedure. The heuristic also works well on 19 newly generated test problems.

A new heuristic for the multi-depot vehicle routing problem that improves upon best-known solutions

SYNOPTIC ABSTRACTIn this paper, the multi-depot vehicle routing problem is reviewed and a new heuristic is presented. The heuristic is fast and simple and improves upon previous best-known solutions. In addition, we generate a variety of new test problems. The new heuristic is shown to perform well on these problems.