Waste Collection Vehicle Routing Problem Research Articles

Tabu search algorithm for solving waste collection vehicle routing problem

This study considers a Waste Collection Vehicle Routing Problem where the situation happens when vehicle must make a complete trip to make disposal operation per day. The Waste Collection Vehicle Routing Problem objective is to decide the best solution where a vehicle should make the collection first between the customers since there exist larger number of customers. The method proposed to solve the Waste Collection Vehicle Routing Problem is by using Tabu Search Algorithm.

Metaheuristics with disposal facility positioning for the waste collection VRP with time windows

This paper improves heuristic algorithms presented in Benjamin and Beasley (Comput Oper Res 37(12):2270–2280, 2010) for solving the waste collection vehicle routing problem with time windows, particularly the real life waste collection benchmark problems from Kim et al. (Comput Oper Res 33(12):3624–3642, 2006). These consist of ten test problems, involving up to 2,092 customers and 19 waste disposal facilities. The main difference between this paper and Benjamin and Beasley (Comput Oper Res 37(12):2270–2280, 2010) is that here we use a disposal facility positioning (DFP) procedure to evaluate routes for our algorithms. Since the problem involves multiple disposal facilities, the objective of DFP is to choose the best disposal facilities to go on the vehicle route. Computational results indicate that our algorithms with DFP produce substantially better quality routes than previous approaches in the literature.

The rollon–rolloff waste collection vehicle routing problem with time windows

This study introduces a rollon–rolloff waste collection vehicle routing problem involving large containers that accumulate huge amounts of garbage at construction sites and shopping districts. In this problem, tractors move one container at a time between customer locations, a depot, disposal facilities, and container storage yards. The complicated constraints discussed in this study arise from having multiple disposal facilities, multiple container storage yards, seven service types of customer demands, different time windows for customer demands and facilities, various types and sizes of containers, and the lunch break of tractor drivers. In addition, real-world issues, such as changing service types, multiple demands at a customer’s location, and tractors with different work schedules, are dealt with. This study proposes a large neighborhood search based iterative heuristic approach consisting of several algorithms for the problem. The effectiveness of the proposed methods is demonstrated by computational experiments using benchmark data, some instances of which are derived from real-world problems.

The Waste Collection Vehicle Routing Problem with Time Windows in a City Logistics Context

Collection of waste is an important logistic activity within any city. In this paper we study how to collect waste in an efficient way. We study the Waste Collection Vehicle Routing Problem with Time Window which is concerned with finding cost optimal routes for garbage trucks such that all garbage bins are emptied and the waste is driven to disposal sites while respecting customer time windows and ensuring that drivers are given the breaks that the law requires. We propose an adaptive large neighborhood search algorithm for solving the problem and illustrate the usefulness of the algorithm by showing that the algorithm can improve the objective of a set of instances from the literature as well as for instances provided by a Danish garbage collection company.

Metaheuristics for the waste collection vehicle routing problem with time windows, driver rest period and multiple disposal facilities

In this problem there is a set of waste disposal facilities, a set of customers at which waste is collected and an unlimited number of homogeneous vehicles based at a single depot. Empty vehicles leave the depot and collect waste from customers, emptying themselves at the waste disposal facilities as and when necessary. Vehicles return to the depot empty. We take into consideration time windows associated with customers, disposal facilities and the depot. We also have a driver rest period. The problem is solved heuristically. A neighbour set is defined for each customer as the set of customers that are close, but with compatible time windows. A procedure that attempts to fully utilise a vehicle is used to obtain an initial solution, with this initial solution being improved using an interchange procedure. We present two metaheuristic algorithms using tabu search and variable neighbourhood search that are based around the neighbour sets. We also present a metaheuristic based on variable neighbourhood tabu search, where the variable neighbourhood is searched via tabu search. Computational results are presented for publicly available waste collection problems involving up to 2092 customers and 19 waste disposal facilities, which indicate that our algorithms produce better quality solutions than previous work presented in the literature.

Waste collection vehicle routing problem with time windows

In this paper, we address a real life waste collection vehicle routing problem with time windows (VRPTW) with consideration of multiple disposal trips and drivers’ lunch breaks. Solomon's well-known insertion algorithm is extended for the problem. While minimizing the number of vehicles and total traveling time is the major objective of vehicle routing problems in the literature, here we also consider the route compactness and workload balancing of a solution since they are very important aspects in practical applications. In order to improve the route compactness and workload balancing, a capacitated clustering-based waste collection VRPTW algorithm is developed. The proposed algorithms have been successfully implemented and deployed for the real life waste collection problems at Waste Management, Inc. A set of waste collection VRPTW benchmark problems is also presented in this paper. Waste collection problems are frequently considered as arc routing problems without time windows. However, that point of view can be applied only to residential waste collection problems. In the waste collection industry, there are three major areas: commercial waste collection, residential waste collection and roll-on-roll-off. In this paper, we mainly focus on the commercial waste collection problem. The problem can be characterized as a variant of VRPTW since commercial waste collection stops may have time windows. The major variation from a standard VRPTW is due to disposal operations and driver's lunch break. When a vehicle is full, it needs to go to one of the disposal facilities (landfill or transfer station). Each vehicle can, and typically does, make multiple disposal trips per day. The purpose of this paper is to introduce the waste collection VRPTW, benchmark problem sets, and a solution approach for the problem. The proposed algorithms have been successfully implemented and deployed for the real life waste collection problems of Waste Management, the leading provider of comprehensive waste management services in North America with nearly 26,000 collection and transfer vehicles.