Rafael Martinelli

Pontifical Catholic University of Rio de Janeiro · Department of Industrial Engineering (IND)

We consider the general multi-vehicle and multi-period Inventory Routing Problem (IRP). A challenging aspect of solving IRPs is how to capture the relationship among the periods where the routing takes place. Once the routes are defined, computing the optimal inventory at each customer on each period amounts to solving a network flow problem. We in...

This paper addresses a complex parallel machine scheduling problem with jobs divided into operations and operations grouped in families. Non-anticipatory family setup times are held at the beginning of each batch, defined by the combination of one setup-time and a sequence of operations from a unique family. Other aspects are also considered in the...

Vehicle routing algorithms usually reformulate the road network into a complete graph in which each arc represents the shortest path between two locations. Studies on time-dependent routing followed this model and therefore defined the speed functions on the complete graph. We argue that this model is often inadequate, in particular for arc routing...

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...

Neighborhood search is a cornerstone of state-of-the-art traveling salesman and vehicle routing metaheuristics. While neighborhood exploration procedures are well developed for problems with individual services, their counterparts for one-to-one pickup-and-delivery problems have been more scarcely studied. A direct extension of classic neighborhood...

The design of cost-effective power line routes is a critical step towards elaborating a consistent network expansion plan. Although several attributes are considered by planning agents, the impact of sharp curvatures is typically neglected within the route design process, thus not accounting for the need for more expensive structures to support the...

The rise of battery-powered vehicles has led to many new technical and methodological hurdles. Among these, the efficient planning of an electric fleet to fulfill passenger transportation requests still represents a major challenge. This is because of the specific constraints of electric vehicles, bound by their battery autonomy and necessity of re...

Neighborhood search is a cornerstone of state-of-the-art traveling salesman and vehicle routing metaheuristics. Whereas neighborhood exploration procedures are well-developed for problems with individual services, their counterparts for one-to-one pickup-and-delivery problems are more scarcely studied. A direct extension of classic neighborhoods is...

School transport is essential to guarantee the access and permanence of students in public schools, especially in rural regions, where students are located in large areas with low density and roads are in precarious situations. The present work aims to apply an Iterated Local Search metaheuristic to route 13,664 students in the rural areas of Rio d...

This paper addresses a parallel machine scheduling problem with non-anticipatory family setup times and batching, considering the task’s stochastic processing times and release dates. The problem arises from a real-life ship scheduling problem in the oil and gas industry. We developed an Iterated Greedy simheuristic with built-in Monte Carlo Simula...

This article describes a new model aiming at optimising short- and medium-term underground mine scheduling. The problem complexity and the frequency at which planners must revise these schedules are among the primary motivations for developing such a model. To address this problem, a Mixed Integer Programming model is proposed with a flexible time...

In this article, we study the Adjacent Quadratic Shortest Path Problem (AQSPP), which consists in finding the shortest path on a directed graph when its total weight component also includes the impact of consecutive arcs. We provide a formal description of the AQSPP and propose an extension of Dijkstra's algorithm (that we denote aqD) for solving A...

Shipowners seek to increase their profits by optimizing the operation of their available fleet, increasing its capacity, and reducing costs while meeting the customers’ demands. Ship routing stands out as a relevant topic of study, especially for tramp shipping companies, due to the high competitivity on this market, which highlights the importance...

This paper addresses a complex parallel machine scheduling problem with jobs divided into operations and operations grouped in families. Non-anticipatory family setup times are held at the beginning of each batch, defined by the combination of one setup-time and a sequence of operations from a unique family. Other aspects are also considered in the...

The rise of battery-powered vehicles for mobility-on-demand leads to many technical and methodological hurdles. Among these, the efficient planning of a shared electric fleet to fulfill passenger transportation requests still represents a major challenge. This is due to the specific constraints of electric vehicles, bound by their autonomy and nece...

In this paper, we address a variant of a batch scheduling problem with identical parallel machines and non-anticipatory family setup times to minimize the total weighted completion time. We developed an ILS and a GRASP matheuristics to solve the problem using a constructive heuristic and two MIP-based neighborhood searches, considering two batch sc...

The use of optimization tools represents a relevant advantage to companies when it comes to improving processes, systems, and performance. In this context, the search for simple and effective programming models for problem-solving contributes to the adaptation of existing models to attend to this increasing demand. The present article aims to plan...

In this paper, we deal with a problem that arises from the oil industry with the need to schedule a pipe laying support vessel fleet responsible for connecting oil wells to production platforms. We model it as an identical parallel machine scheduling problem, considering a particular case where jobs are composed of intersecting sets of operations a...

In this paper, we address a variant of a batch scheduling problem with identical parallel machines and non-anticipatory family setup times to minimize the total weighted completion time. We developed an ILS and a GRASP matheuristics to solve the problem using a constructive heuristic and two MIP-based neighborhood searches, considering two batch sc...

We present a mixed-integer programming model for solving the long-term planning problem of an underground mine. This model, which establishes the sequence of mining for a horizon of 20 years, determines which lens of the geological model will be mined and in what order, while respecting the operational constraints. For each lens to be mined, a spec...

Vehicle routing algorithms usually reformulate the road network into a complete graph in which each arc represents the shortest path between two locations. Studies on time-dependent routing followed this model and therefore defined the speed functions on the complete graph. We argue that this model is often inadequate, in particular for arc routing...

Our work intend to provide a tertiary review of the literature related to green logistics, answering the following research questions: What are the main green logistics reviews? What are their characteristics? What are the objectives of the studies in which researchers are most involved? And what are the main gaps for future research?

In this paper, we propose a stochastic programming approach to perform optimal and robust offshore flight scheduling from a service level perspective, reducing flight delays. The two-stage stochastic programming is reduced to a deterministic equivalent linear program and, considering the combinatorial characteristic of scheduling problems, we use S...

Recent studies in maritime logistics have introduced a general ship routing problem and a benchmark suite based on real shipping segments, considering pickups and deliveries, cargo selection, ship-dependent starting locations, travel times and costs, time windows, and incompatibility constraints, among other features. Together, these characteristic...

The partial digest problem consists in retrieving the positions of a set of points on the real line from their unlabeled pairwise distances. This problem is critical for DNA sequencing, as well as for phase retrieval in X-ray crystallography. When some of the distances are missing, this problem generalizes into a “minimum distance superset problem”...

We consider the multi-vehicle one-to-one pickup and delivery problem with split loads, a NP-hard problem linked with a variety of applications for bulk product transportation, bike-sharing systems and inventory re-balancing. This problem is notoriously difficult due to the interaction of two challenging vehicle routing attributes, "pickups and deli...

We consider the multi-vehicle one-to-one pickup and delivery problem with split loads, a NP-hard problem linked with a variety of applications for bulk product transportation, bike-sharing systems and inventory re-balancing. This problem is notoriously difficult due to the interaction of two challenging vehicle routing attributes, "pickups and deli...

Logistics is a science widely recognized as a value-added component for organizations and their products and services as it optimizes the use of resources, minimizes costs and maximizes level of service by coordinating activities such as transportation, inventory management and material handling. In traditional systems, transportation streams from...

We consider a vehicle routing problem which seeks to minimize cost subject to service level constraints on several groups of deliveries. This problem captures some essential challenges faced by a logistics provider which operates transportation services for a limited number of partners and should respect contractual obligations on service levels. T...

We consider a vehicle routing problem which seeks to minimize cost subject to service level constraints on several groups of deliveries. This problem captures some essential challenges faced by a logistics provider which operates transportation services for a limited number of partners and should respect contractual obligations on service levels. T...

In this article we introduce the quadratic capacitated vehicle routing problem (QCVRP) motivated by two applications in engineering and logistics: the capacitated vehicle routing problem with angle penalties (angle-CVRP) and the capacitated vehicle routing problem with reload costs (CVRP-RC). We introduce a three-index vehicle-flow formulation of t...

Column generation is involved in the current most efficient approaches to routing problems. Set partitioning formulations model routing problems by considering all possible routes and selecting a subset that visits all customers. These formulations often produce tight lower bounds and require column generation for their pricing step. The bounds in...

This article presents an exact algorithm for the multi-depot vehicle routing problem (MDVRP) under capacity and route length constraints. The MDVRP is formulated using a vehicle-flow and a set-partitioning formulation, both of which are exploited at different stages of the algorithm. The lower bound computed with the vehicle-flow formulation is use...

The Capacitated Arc Routing Problem (CARP) stands among the hardest combinatorial problems to solve or to find high quality solutions. This becomes even more true when dealing with large instances. This paper investigates methods to improve on lower and upper bounds of instances on graphs with over 200 vertices and 300 edges, dimensions that, today...

Arc routing problems are among the most challenging combinatorial optimization problems. We tackle the Capacitated Arc Routing Problem where demands are spread over a subset of the edges of a given graph, called the required edge set. Costs for traversing edges, demands on the required ones and the capacity of the available identical vehicles at a...

Arc routing problems are among the most challenging combinatorial optimization problems. We tackle the Capacitated Arc Routing Problem where demands are spread over a subset of the edges of a given graph, called the required edge set. Costs for traversing edges, demands on the required ones and the capacity of the available identical vehicles at a...

Planning in Railway Logistic is an activity with growing importance. This is due to the high costs of investment to increase the railway capacity. Nevertheless, planning in this context is a cumbersome task, since a precise representation is necessary to consider most relevant points in this activity. Mathematical programming is becoming one of the...