A variable neighborhood search for the green vehicle routing problem with two-dimensional loading constraints and split delivery

We address the Green Vehicle Routing Problem with Two-Dimensional Loading Constraints and Split Delivery (G2L-SDVRP), which extends the split delivery vehicle routing problem to include customer demands represented by two-dimensional, rectangular items. We aim to minimize carbon dioxide (CO\(_2\)) emissions instead of travel distance, a critical issue in contemporary logistics activities. The CO\(_2\) emission rate … Read more

An Efficient Pixel-based Packing Algorithm for Additive Manufacturing Production Planning

Additive Manufacturing (AM), the technology of rapid prototyping directly from 3D digital models, has made a significant impact on both academia and industry. When facing the growing demand of AM services, AM production planning (AMPP) plays a vital role in reducing makespan and costs for AM service companies. This research focuses on the AMPP problem … Read more

Minimizing earliness-tardiness costs in supplier networks – A Just-in-time Truck Routing Problem

We consider a routing problem where orders are transported just-in-time from several suppliers to an original equipment manufacturer (OEM). This implies that shipments cannot be picked up before their release date when they are ready at the supplier and should be delivered as close as possible to their due date to the OEM. Every shipment … Read more

The Combinatorial Brain Surgeon: Pruning Weights That Cancel One Another in Neural Networks

Neural networks tend to achieve better accuracy with training if they are larger — even if the resulting models are overparameterized. Nevertheless, carefully removing such excess parameters before, during, or after training may also produce models with similar or even improved accuracy. In many cases, that can be curiously achieved by heuristics as simple as … Read more

Heuristic approaches for split delivery vehicle routing problems

We propose a matheuristic approach to solve split delivery variants of the vehicle routing problem (VRP). The proposed method is based on the use of several mathematical programming components within an Iterated Local Search metaheuristic framework. In addition to well-known VRP local search heuristics, we include new types of improvement and perturbation strategies that are … Read more

An Efficient Tabu Search Algorithm for the Tool Indexing Problem

In this paper, we look at the tool indexing problem in which a single copy of each tool is allowed in the tool magazine. We develop problem specific methods to search the neighborhood efficiently and design a Tabu Search algorithm based on them. Computational experiments show that our algorithm is competent. CitationIndian Institute of Management … Read more

Metaheuristic, Models and Software for the Heterogeneous Fleet Pickup and Delivery Problem with Split Loads

This paper addresses a rich variant of the vehicle routing problem (VRP) that involves pickup and delivery activities, customer time windows, heterogeneous fleet, multiple products and the possibility of splitting a customer demand among several routes. This variant generalizes traditional VRP variants by incorporating features that are commonly found in practice. We present two mixed-integer … Read more

Decomposition strategies for vehicle routing heuristics

Decomposition techniques are an important component of modern heuristics for large instances of vehicle routing problems. The current literature lacks a characterisation of decomposition strategies and a systematic investigation of their impact when integrated into state-of-the-art heuristics. This paper fills this gap: we discuss the main characteristics of decomposition techniques in vehicle routing heuristics, highlight … Read more

An Adaptive and Near Parameter-free BRKGA Using Q-Learning Method

The Biased Random-Key Genetic Algorithm (BRKGA) is an efficient metaheuristic to solve combinatorial optimization problems but requires parameter tuning so the intensification and diversification of the algorithm work in a balanced way. There is, however, not only one optimal parameter configuration, and the best configuration may differ according to the stages of the evolutionary process. … Read more