IMPROVEMENT OF PICK-UP ROUTES FOR AN INTERNATIONAL SHIPPING ENTERPRISE BY USING A HEURISTIC METHOD

Route design is an important factor for the management of supply and logistics operations required by production processes. In this work the re-design of pick-up/delivery routes for an international shipping enterprise was performed to improve vehicle utilization for pick-up/delivery operations and reduce transportation time. The re-design of the routes was accomplished by using a random heuristic method. As a result, it was obtained that pickup/delivery for all clients can be performed with a small number of vehicles. Also, vehicle utilization can be maximized over 90.00% with a significant reduction in total transportation time which leads to decrease operational cost. The additional available time then can be used to cover a higher number of clients, increasing the presence of the enterprise in the market

HEURISTIC FOR ASYMMETRIC CAPACITATED VEHICLE ROUTING PROBLEM

The vehicle routing problem (VRP) is commonly defined as the problem of designing optimal delivery or collection routes from one or several depots to a set of geographically scattered customers, under a variety of side conditions. This problem is generally described through a graph, whose arcs represent the road sections and vertices correspond to the depot and customer locations. The arcs (and consequently the corresponding graph) can be directed or undirected, depending on whether they can be traversed in only one direction or in both directions. Since each arc is associated with a cost then if the graph is directed, the cost matrix is asymmetric and the corresponding problem is called asymmetric vehicle routing problem (AVRP). Although the symmetric problems are special cases of the asymmetric ones, the latter were much less studied in the literature. In this paper, a type of problem, called the Asymmetric Capacitated Vehicle Routing Problem (ACVRP) is discussed and a heuristic algorithm is proposed to solve the problem. Keywords: Vehicle Routing, Asymmetric, Capacitated, Heuristi

An Efficiency Improvement Approach to Reduce Transportation Costs: An Application

The reduction of transportation costs is an important issue for many companies that need to stay competitive. This work describes the application of a scheme for increasing transportation efficiency to achieve this purpose. This scheme is developed around a modified version of the Operational Equipment Effectiveness index used in TPM. This is adapted to be used as the main performance measure in transport operations. Availability, performance and quality wastes are identified using Value Stream Mapping of the operation. The implementation is carried out in the routing operation of a Mexican firm. The improvement initiatives are still in progress but the projected and available results are provided

Modelling and solving logistical problems with combinatorial optimization: case Parmatic

This paper deals with various logistical optimisation problems by modelling them with modified versions of, or problems related to, the Vehicle Routing Problem. The problem is modelled as an Asymmetrical Capacitated Vehicle Routing Problem with multiple vehicles, the number of vehicles being found from solving the Bin Packing Problem. First, a linear programming formulation is constructed. Then an object-oriented programming implementation is derived from the original formulation, and implemented into a tool used to solve an empirical case from a construction company. The tool used is a Java-based application developed by the author

Job Selection in a Network of Autonomous UAVs for Delivery of Goods

This article analyzes two classes of job selection policies that control how a network of autonomous aerial vehicles delivers goods from depots to customers. Customer requests (jobs) occur according to a spatio-temporal stochastic process not known by the system. If job selection uses a policy in which the first job (FJ) is served first, the system may collapse to instability by removing just one vehicle. Policies that serve the nearest job (NJ) first show such threshold behavior only in some settings and can be implemented in a distributed manner. The timing of job selection has significant impact on delivery time and stability for NJ while it has no impact for FJ. Based on these findings we introduce a methodological approach for decision-making support to set up and operate such a system, taking into account the trade-off between monetary cost and service quality. In particular, we compute a lower bound for the infrastructure expenditure required to achieve a certain expected delivery time. The approach includes three time horizons: long-term decisions on the number of depots to deploy in the service area, mid-term decisions on the number of vehicles to use, and short-term decisions on the policy to operate the vehicles

Ant Colony Optimization for the Electric Vehicle Routing Problem

Ant colony optimization (ACO) algorithms have proved to be powerful tools to solve difficult optimization problems. In this paper, ACO is applied to the electric vehicle routing problem (EVRP). New challenges arise with the consideration of electric vehicles instead of conventional vehicles because their energy level is affected by several uncertain factors. Therefore, a feasible route of an electric vehicle (EV) has to consider visit(s) to recharging station(s) during its daily operation (if needed). A look ahead strategy is incorporated into the proposed ACO for EVRP (ACO-EVRP) that estimates whether at any time EVs have within their range a recharging station. From the simulation results on several benchmark problems it is shown that the proposed ACO-EVRP approach is able to output feasible routes, in terms of energy, for a fleet of EVs