Constructive heuristics for automatic warehouse scheduling
Ivan Davydov, Yury Kochetov
We consider a real-life problem which arise in an industrial process of big electronic device manufacturer. A warehouse, which stores the finished products is involved into the orders packing and delivery process. Each order should process through two stages to be prepared for delivery. During the first stage, picking, the ordered goods have to be extracted from the storage. During the second stage these goods have to be packed into the boxes and transferred to the delivery service. The problem is to arrange the schedule and the way the orders have to process through the stages, in order to maximize the throughput of the warehouse. We propose a set of constructive heuristics and hybrid approaches for this problem and discuss the results of computational experiments.
A GRASP/VND Heuristic for the Heterogeneous Fleet Vehicle Routing Problem with Time Windows
Lucía Barrero, Franco Robledo, Pablo Romero, Rodrigo Viera, Sebastián Laborde
The Heterogeneous Fleet Vehicle Routing Problem with Time Windows (HFVRPTW) is here introduced. This combinatorial optimization problem is an extension of the well-known Vehicle Routing Problem (VRP), which belongs to the NP-Hard class. As a corollary, our problem belongs to this class, a fact that promotes the development of approximative methods. A mathematical programming formulation for the HFVRPTW is presented, and an exact solution method using CPLEX is implemented. A GRASP/VND methodology is also developed, combining five different local searches. The effectiveness of our proposal is studied in relation with the exact solver. Our proposal outperforms the exact CPLEX in terms of CPU times, and finds even better solutions under large-sized instances, where the exact solver halts after ten hours of continuous execution.
A Hybrid VNS for the Multi-Product Maritime Inventory Routing Problem
Nathalie Sanghikian, Rafael Martinelli, Victor Abu-Marrrul
In a growth scenario of the world economy, it is essential to increase the integration between the different actors in the companies' supply chain, reducing operational costs and improving efficiency. Ship routing is a crucial part of this integration regarding global maritime commerce. In this work, we present a hybrid VNS metaheuristic to tackle a real Maritime Inventory Routing Problem (MIRP) in a company that explores oil and gas in the Brazilian offshore basin. In the methodology proposed, a linear mathematical model is embedded in the local search procedure to minimize inventory costs. The approach, validated within realistic data, provides low and not regular inventory violation. When compared with a previously developed method, it presents an improved performance, with reduced costs and computational time.
Less is more: basic variable neighborhood search for a fair scheduling problem
Caroline Rocha, Bruno J. S. Pessoa, Daniel Aloise
The Weighted Fair Sequences Problem (WFSP) is an optimization problem that has been recently proposed in the literature. It covers a large number of applications in different areas, ranging from automobile production on a mixed-model assembly line to the sequencing of interactive applications to be aired in a Digital TV environment. This work presents a basic variable neighborhood search heuristic for approaching the WFSP, following the recently proposed "Less is More Approach". Computational experiments demonstrate that the proposed algorithm is efficient