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

A constructive heuristic for the multi-compartment vehicle routing problem: an approach for a fuel distribution company

In this paper, we suggest a Decision Support System (DSS) for route planning. This DSS was developed in a real context in a fuel distribution company. This company distributes three types of fuel through multi-compartment vehicles with limited capacity, and satisfying delivery time windows imposed by the customers. Two approaches for this problem were considered: The first one considers the route planning without replenishments while the second one considers the multi-trip case. The solution method is based on a Clarke and Wright savings algorithm incorporating all the constraints referred to above. Both approaches were tested using real instances. The savings for the company, in terms of the distribution process, were identified in the computational results. The DSS may provide an effective support to a complex decision problem.This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio

A multiple type bike repositioning problem

This paper investigates a new static bicycle repositioning problem in which multiple types of bikes are considered. Some types of bikes that are in short supply at a station can be substituted by other types, whereas some types of bikes can occupy the spaces of other types in the vehicle during repositioning. These activities provide two new strategies, substitution and occupancy, which are examined in this paper. The problem is formulated as a mixed-integer linear programming problem to minimize the total cost, which consists of the route travel cost, penalties due to unmet demand, and penalties associated with the substitution and occupancy strategies. A combined hybrid genetic algorithm is proposed to solve this problem. This solution algorithm consists of (i) a modified version of a hybrid genetic search with adaptive diversity control to determine routing decisions and (ii) a proposed greedy heuristic to determine the loading and unloading instructions at each visited station and the substitution and occupancy strategies. The results show that the proposed method can provide high-quality solutions with short computing times. Using small examples, this paper also reveals problem properties and repositioning strategies in bike sharing systems with multiple types of bikes.published_or_final_versio

Sustainable maritime crude oil transportation: a split pickup and split delivery problem with time windows

This paper studies a novel sustainable vessel routing problem modeling considering the multi-compartment, split pickup and split delivery, and time windows concepts. In the presented problem, oil tankers transport crude oil from supply ports to demand ports around the globe. The objective is to find ship routes, as well as port arrival and departure times, in a way that minimizes transportation costs. As a second objective, we considered the sustainability aspect by minimizing the vessel energy efficiency operational indicator. Multiple products are transported by a heterogeneous fleet of tankers. Small realistic test instances are solved with the exact method