
Túlio A. M. ToffoloFederal University of Ouro Preto · Department of Computing
Túlio A. M. Toffolo
PhD
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42
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Publications (42)
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...
Collaborative delivery employing drones in last-mile delivery has been an extensively studied topic in recent years. In this paper, it is studied Truck-Drone Delivery Problems (TDDPs) in which a traditional delivery truck is gathered with a drone to cut delivery times and costs. The vehicles work together in a hybrid operation involving one drone l...
This paper addresses the general and challenging Sports Timetabling Problem proposed during the International Timetabling Competition of 2021 (ITC2021). The problem is expressed in a flexible format which enables modeling a number of real-world constraints that often occur in Sports Timetabling. An integer programming (IP) formulation and a fix-and...
The Weapon-Target Assignment (WTA) problem aims to assign a set of weapons to a number of assets (targets), such that the expected value of survived targets is minimized. The WTA problem is a nonlinear combinatorial optimization problem known to be NP-hard. This paper applies several existing techniques to linearize the WTA problem. One linearizati...
This paper introduces the Vessel Swap-Body Routing problem (VSBR), a generalization of the pickup and delivery problem with time windows, which considers freight distribution between ports located throughout an inland waterway network. Subject to time windows and precedence constraints, each customer request is associated with a number of container...
The two-echelon location routing problem (2E-LRP) arises in freight distribution when goods available at different origins are delivered to their respective destinations via intermediate facilities. The literature concerning the 2E-LRP considers freight capacities of vehicles to be scalars, while customer demands are additive volumes of individual...
The Flying Sidekick Traveling Salesman Problem (FSTSP) considers a delivery system composed by a truck and a drone. The drone launches from the truck with a single package to deliver to a customer. Each drone must return to the truck to recharge batteries, pick up another package, and launch again to a new customer location. This work proposes a no...
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...
Decision support systems and automated planning have become essential for the effective management of seaport container terminals. Due to ever-increasing levels of maritime traffic and freight transportation, terminals are expected to facilitate their intra-yard operations while respecting tighter vessel schedules. Employed models must therefore be...
In this paper, we introduce the double traveling salesman problem with partial last‐in‐first‐out loading constraints (DTSPPL). It is a pickup‐and‐delivery single‐vehicle routing problem, where all pickup operations must be performed before any delivery operation because the pickup‐and‐delivery areas are geographically separated. The vehicle collect...
Tank terminals play a significant role in the storage and international transportation of goods such as liquids and gases. This paper focuses on a real-world problem where trucks must be assigned to loading stations which connect to tanks containing the product to (un)load. The typically limited operational space results in a specific type of block...
In this paper, we introduce the Double Traveling Salesman Problem with Partial Last-In-First-Out Loading Constraints (DTSPPL), a pickup-and-delivery single-vehicle routing problem where all pickup operations must be performed before any delivery one because the pickup and delivery areas are geographically separated. The vehicle collects items in th...
The sport teams grouping problem (STGP) concerns the assignment of sport teams to round-robin tournaments. The objective is to minimize the total travel distance of the participating teams while simultaneously respecting fairness constraints. The STGP is an NP-Hard combinatorial optimization problem highly relevant in practice. This paper investiga...
When applying periodic re-optimization for handling a dynamic scheduling problem, the objective of the problem solved in each period (its short term objective) significantly impacts the quality of final solutions (its long term solutions). Meanwhile, designing a short term objective consistent with the dynamic problem's long term objective remains...
Three-dimensional Cutting and Packing Problems consist of a set of items that must be placed inside one or more larger items (containers). Such problems enforce non-overlapping constraints which ensure that the smaller items being assigned must completely fit inside their respective container. Despite extensive preexisting literature, there is the...
This work addresses the unrelated parallel machine scheduling problem with sequence-dependent setup times, in which a set of jobs must be scheduled for execution by one of several available machines. Each job has a machine-dependent processing time. Furthermore, given multiple jobs, there are additional setup times, which vary based on the sequence...
Crane-operated warehouses constitute an essential asset for the many industries which must temporarily store products on their way from manufacturers to consumers. Such warehouses are a practical necessity rather than an explicitly desired service and they introduce significant operational costs which should be minimized. The problem addressed by t...
The Traveling Umpire Problem (TUP) is a combinatorial optimization problem concerning the assignment of umpires to the games of a fixed double round-robin tournament. The TUP draws inspiration from the real world multi-objective Major League Baseball (MLB) umpire scheduling problem, but is, however, restricted to the single objective of minimizing...
We investigate a structural decomposition for the capacitated vehicle routing problem (CVRP) based on vehicle-to-customer "assignment" and visits "sequencing" decision variables. We show that an heuristic search focused on assignment decisions with a systematic optimal choice of sequences (using Concorde TSP solver) during each move evaluation is p...
We investigate a structural decomposition for the capacitated vehicle routing problem (CVRP) based on vehicle-to-customer "assignment" and visits "sequencing" decision variables. We show that an heuristic search focused on assignment decisions with a systematic optimal choice of sequences (using Concorde TSP solver) during each move evaluation is p...
This work presents the stochastic local search method for the Swap-Body Vehicle Routing Problem (SB-VRP) that won the First VeRoLog Solver Challenge. The SB-VRP, proposed on the occasion of the challenge, is a generalization of the classical Vehicle Routing Problem (VRP) in which customers are served by vehicles whose sizes may be enlarged via the...
The Nurse Rostering Problem (NRP) is an optimization problem where nurses with specific skills must be assigned shifts in a schedule. The objective is to obtain a feasible solution while minimizing the number of soft constraint violations. This work presents a Variable Neighborhood Search accelerated Column Generation procedure for the NRP in addit...
The traditional set of manufacturing scheduling problems concern general and easy-to-measure economic objectives such as makespan and tardiness. The variable nature of energy costs over the course of the day remains mostly ignored by most previous research. This variability should not be considered an added complexity, but rather an opportunity for...
Efficient container loading has the potential to considerably reduce logistics and transportation costs. The container loading problem is computationally complex and, despite extensive academic effort, there remains room for algorithm improvement. Real-world problems are not always addressed satisfactorily primarily due to the large number of compl...
Methods based on Stochastic Local Search (SLS) have been ranked as the best heuristics available for many hard combinatorial optimization problems. The design of SLS methods which use many neighborhoods poses difficult questions regarding the exploration of these neighborhoods: how much computational effort should be invested in each neighborhood?...
The Traveling Umpire Problem (TUP) is an optimization problem in which umpires have to be assigned to games in a double round robin tournament. The objective is to obtain a solution with minimum total travel distance over all umpires, while respecting hard constraints on assignments and sequences. Up till now, no general nor dedicated algorithm was...
The project scheduling problem (PSP) is the subject of several studies in computer science, mathematics, and operations research because of the hardness of solving it and its practical importance. This work tackles an extended version of the problem known as the multimode resource-constrained multiproject scheduling problem. A solution to this prob...
This work presents a local search approach to the High School Timetabling Problem. The addressed timetabling model is the one stated in the Third International Timetabling Competition (ITC 2011), which considered many instances from educational institutions around the world and attracted seventeen competitors. Our team, named GOAL (Group of Optimiz...
This work presents Integer Programming (IP) techniques to tackle the problem of the International Nurse Rostering Competition. Starting from a compact and monolithic formulation in which the current generation of solvers performs poorly, improved cut generation strategies and primal heuristics are proposed and evaluated. A large number of computati...
The High School Timetabling Problem consists in assigning timeslots and resources to events, satisfying constraints which heavily depend on the specific institution. This work deals with the problem of the ongoing III International Timetabling Competition (ITC), which includes a diverse set of instances from many educational institutions around the...
This work presents the study of mathematical programming heuristics for a variant of the
classical Nurse Rostering Problem, which considers the work distribution in shifts in a given
time period. Since nursing services cost represents are very significant in a hospital budget it
is essential to have a solid planning strategy. Specifically, it is im...
We propose algorithms to compute tight lower bounds and high quality upper bounds (UBs) for the multilevel capacitated minimum spanning tree problem. We first develop a branch-and-cut algorithm, introducing some new features: (i) the exact separation of cuts corresponding to some master equality polyhedra found in the formulation; (ii) the separati...
We propose a GRASP using an hybrid heuristic-subproblem optimization approach for the Multi-Level Capacitated Minimum Spanning
Tree (MLCMST) problem. The motivation behind such approach is that to evaluate moves rearranging the configuration of a subset
of nodes may require to solve a smaller-sized MLCMST instance. We thus use heuristic rules to de...
Neste trabalho são apresentados algoritmos baseados nas metaheuristicas Simulated Annealing e Iterated Local Search para resolver o problema de programação mensal de tripulações de ônibus urbano.
We propose efficient algorithms to compute tight lower bounds and high quality upper bounds for the Multi-Level Capacitated Minimum Spanning Tree problem. We first develop a branch-and-cut algorithm for the problem. This algorithm is able to solve instances of medium size and to provide tight lower bounds for larger ones. We then use the branch-and...