Waste Collection Vehicle Routing Problem: Literature Review

Waste generation is an issue which has caused wide public concern in modern societies, not only for the quantitative rise of the amount of waste generated, but also for the increasing complexity of some products and components. Waste collection is a highly relevant activity in the reverse logistics system and how to collect waste in an efficient way is an area that needs to be improved. This paper analyzes the major contribution about Waste Collection Vehicle Routing Problem (WCVRP) in literature. Based on a classification of waste collection (residential, commercial and industrial), firstly the key findings for these three types of waste collection are presented. Therefore, according to the model (Node Routing Problems and Arc Routing problems) used to represent WCVRP, different methods and techniques are analyzed in this paper to solve WCVRP. This paper attempts to serve as a roadmap of research literature produced in the field of WCVRP

Lower bounds for the mixed capacitated arc routing problem

Capacitated arc routing problems (CARP) arise in distribution or collecting problems where activities are performed by vehicles, with limited capacity, and are continuously distributed along some pre-defined links of a network. The CARP is defined either as an undirected problem or as a directed problem depending on whether the required links are undirected or directed. The mixed capacitated arc routing problem (MCARP) models a more realistic scenario since it considers directed as well as undirected required links in the associated network. We present a compact flow based model for the MCARP. Due to its large number of variables and constraints, we have created an aggregated version of the original model. Although this model is no longer valid, we show that it provides the same linear programming bound than the original model. Different sets of valid inequalities are also derived. The quality of the models is tested on benchmark instances with quite promising results..info:eu-repo/semantics/publishedVersio

Efficient routing of snow removal vehicles

This research addresses the problem of finding a minimum cost set of routes for vehicles in a road network subject to some constraints. Extensions, such as multiple service requirements, and mixed networks have been considered. Variations of this problem exist in many practical applications such as snow removal, refuse collection, mail delivery, etc. An exact algorithm was developed using integer programming to solve small size problems. Since the problem is NP-hard, a heuristic algorithm needs to be developed. An algorithm was developed based on the Greedy Randomized Adaptive Search Procedure (GRASP) heuristic, in which each replication consists of applying a construction heuristic to find feasible and good quality solutions, followed by a local search heuristic. A simulated annealing heuristic was developed to improve the solutions obtained from the construction heuristic. The best overall solution was selected from the results of several replications. The heuristic was tested on four sets of problem instances (total of 115 instances) obtained from the literature. The simulated annealing heuristic was able to achieve average improvements of up to 26.36% over the construction results on these problem instances. The results obtained with the developed heuristic were compared to the results obtained with recent heuristics developed by other authors. The developed heuristic improved the best-known solution found by other authors on 18 of the 115 instances and matched the results on 89 of those instances. It worked specially better with larger problems. The average deviations to known lower bounds for all four datasets were found to range between 0.21 and 2.61%

Deliver or hold: Approximation Algorithms for the Periodic Inventory Routing Problem

The inventory routing problem involves trading off inventory holding costs at client locations with vehicle routing costs to deliver frequently from a single central depot to meet deterministic client demands over a finite planing horizon. In this paper, we consider periodic solutions that visit clients in one of several specified frequencies, and focus on the case when the frequencies of visiting nodes are nested. We give the first constant-factor approximation algorithms for designing optimum nested periodic schedules for the problem with no limit on vehicle capacities by simple reductions to prize-collecting network design problems. For instance, we present a 2.55-approximation algorithm for the minimum-cost nested periodic schedule where the vehicle routes are modeled as minimum Steiner trees. We also show a general reduction from the capacitated problem where all vehicles have the same capacity to the uncapacitated version with a slight loss in performance. This reduction gives a 4.55-approximation for the capacitated problem. In addition, we prove several structural results relating the values of optimal policies of various types

School bus selection, routing and scheduling.

The aim of this thesis is to develop formulations and exact algorithms for the school bus routing and scheduling problem and to develop an integrated software implementation using Xpress-MP/CPLEX and ArcGIS of ESRI, a geographical information system software package. In this thesis, bus flow, single commodity flow, two-commodity flow, multi-commodity flow, and time window formulations have been developed. They capture all of the important elements of the School Bus Routing and Scheduling Problem (SBRSP) including homogeneous or heterogeneous bus fleets, the identification of bus stops from a large set of potential bus stops, and the assignment of students to stops and stops to routes. They allow for the one stop-one bus and one stop-multi bus scenarios. Each formulation of the SBRSP has a linear programming relaxation and we present the relationships among them. We present a Branch-and-Cut exact algorithm which makes use of new linearization techniques, new valid inequalities, and the first valid equalities. We develop an integrated software package that is based on Geographical Information System (GIS) map-based interface, linking to an Xpress-MP/CPLEX solver. The interface between GIS and Xpress-MP is written in VBA and VC++.Dept. of Mathematics and Statistics. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2005 .K4. Source: Dissertation Abstracts International, Volume: 66-11, Section: B, page: 6250. Thesis (Ph.D.)--University of Windsor (Canada), 2005

A case study of two-echelon multi-depot vehicle routing problem

The Vehicle Routing Problem (VRP) is a classic combinatorial optimization problem and a topic still studied for practical applications. Current research focuses on single echelon distribution systems such as distribution centers serving customers. However, in typical distribution, goods flows among regional distribution centers, local warehouses and customers, defined as a two-echelon network. The two-echelon multiple depot VRP problem is documented and applied to two stages illustrated by a small scale computational example. In the first stage, the simulated annealing algorithm is employed to determine the routes between local warehouses and final customers. For the second stage, trial-and-error is applied to obtain the number and location of regional distribution centers and the routes between regional distribution centers and local warehouses. Matlab is utilized to simulate annealing iterations and cost functions are analyzed. The convergence tendency of simulated annealing is depicted in figures by Matlab coding. Contributions include demonstration between the SA algorithm and a specific combinatorial optimization problem, and an application of the algorithm

On the inventory routing problem with stationary stochastic demand rate

One of the most significant paradigm shifts of present business management is that individual businesses no longer participate as solely independent entities, but rather as supply chains (Lambert and Cooper, 2000). Therefore, the management of multiple relationships across the supply chain such as flow of materials, information, and finances is being referred to as supply chain management (SCM). SCM involves coordinating and integrating these multiple relationships within and among companies, so that it can improve the global performance of the supply chain. In this dissertation, we discuss the issue of integrating the two processes in the supply chain related, respectively, to inventory management and routing policies. The challenging problem of coordinating the inventory management and transportation planning decisions in the same time, is known as the inventory routing problem (IRP). The IRP is one of the challenging optimization problems in logis-tics and supply chain management. It aims at optimally integrating inventory control and vehicle routing operations in a supply network. In general, IRP arises as an underlying optimization problem in situations involving simultaneous optimization of inventory and distribution decisions. Its main goal is to determine an optimal distribution policy, consisting of a set of vehicle routes, delivery quantities and delivery times that minimizes the total inventory holding and transportation costs. This is a typical logistical optimization problem that arises in supply chains implementing a vendor managed inventory (VMI) policy. VMI is an agreement between a supplier and his regular retailers according to which retailers agree to the alternative that the supplier decides the timing and size of the deliveries. This agreement grants the supplier the full authority to manage inventories at his retailers'. This allows the supplier to act proactively and take responsibility for the inventory management of his regular retailers, instead of reacting to the orders placed by these retailers. In practice, implementing policies such as VMI has proven to considerably improve the overall performance of the supply network, see for example Lee and Seungjin (2008), Andersson et al. (2010) and Coelho et al. (2014). This dissertation focuses mainly on the single-warehouse, multiple-retailer (SWMR) system, in which a supplier serves a set of retailers from a single warehouse. In the first situation, we assume that all retailers face a deterministic, constant demand rate and in the second condition, we assume that all retailers consume the product at a stochastic stationary rate. The primary objective is to decide when and how many units to be delivered from the supplier to the warehouse and from the warehouse to retailers so as to minimize total transportation and inventory holding costs over the finite horizon without any shortages