Models and exact methods for the integration of scheduling in cross-docking and container loading problems

• Grant number: 17/01097-9
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Start date: August 01, 2017
• End date: July 31, 2018
• Field of knowledge: Engineering - Production Engineering - Operational Research
• Principal Investigator: Franklina Maria Bragion de Toledo
• Grantee: Pedro Belin Castellucci
• Supervisor: Alysson Machado Costa
• Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• Institution abroad: University of Melbourne, Australia
• Associated to the scholarship: 15/15024-8 - Cross-docking and packing integration problem with environmental aspects, BP.DR

Abstract

One of the goals of city logistics is to provide transportation of goods in urban environments minimising negative side effects to the population. For this, multi-tiered logistic systems are an efficient option. In such systems, goods are consolidated in cross-docks in the outer tiers and vehicles suited to denser urban areas perform the last-mile delivery. In this sense, we aim at integrating operational aspects of cross-docking and container loading problems. Specifically, our goal is to develop models and exact methods to position boxes into a container contemplating scheduling of inbound and outbound vehicles in a cross-dock.

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

CASTELLUCCI, PEDRO B.; TOLEDO, FRANKLINA M. B.; COSTA, ALYSSON M.. Output maximization container loading problem with time availability constraints. OPERATIONS RESEARCH PERSPECTIVES, v. 6, 2019. (13/07375-0, 18/07240-0, 15/15024-8, 17/01097-9)

CASTELLUCCI, PEDRO B.; COSTA, ALYSSON M.; TOLEDO, FRANKLINA. Network scheduling problem with cross-docking and loading constraints. Computers & Operations Research, v. 132, AUG 2021. (15/15024-8, 13/07375-0, 17/01097-9)