Luca Di Gaspero

University of Udine | UNIUD · Polytechnic Department of Engineering and Architecture

Purpose: Over time, the focus on supportive and geriatric care has shifted from being predominantly provided in institutional settings like nursing or rest homes to be delivered within the homes of the patients. Trained caregivers now provide home healthcare services by visiting patients in their own homes and carrying out specific services based o...

This study investigates the application of reinforcement learning for the adaptive tuning of neighborhood probabilities in stochastic multi-neighborhood search. The aim is to provide a more flexible and robust tuning method for heterogeneous scenarios than traditional offline tuning. We propose a novel mix of learning components for multi-neighborh...

Emergency Medical Services (EMS) are crucial in delivering timely and effective medical care to patients in need. However, the complex and dynamic nature of operations poses challenges for decision-making processes at strategic, tactical, and operational levels. This paper proposes an action-driven strategy for EMS management, employing a multi-obj...

We propose a portfolio of exact and metaheuristic methods for the rich examination timetabling problem introduced by Battistutta et al. (in: Hebrard, Musliu (eds) 17th International conference on the integration of constraint programming, artificial intelligence, and operations research (CPAIOR-2020), LNCS, vol 12296. Springer, Berlin, pp 69–81, 20...

We propose the development and application of a multi-objective biased random-key genetic algorithm to identify sets of ambulance locations in a rural-mountainous area. The algorithm involves a discrete event simulator to estimate the objective functions, thus we want to minimize the response time while maximizing the area served within the standar...

Crowdsourcing is the practice of outsourcing a task that would otherwise be performed by one or a few experts to a crowd of individuals. It is often used to collect large amounts of manually created labels that form datasets for training and evaluating supervised machine learning models. When designing a (micro-task) crowdsourcing experiment, it is...

We propose a survey of the research contributions on the field of Educational Timetabling with a specific focus on “standard” formulations and the corresponding benchmark instances. We identify six of such formulations and we discuss their features, pointing out their relevance and usability. Other available formulations and datasets are also revie...

We describe the solver that we developed for the Sports Timetabling Competition ITC2021, a three-stage simulated annealing approach, that makes use of a portfolio of six different neighborhoods. Five of these neighborhoods are taken from the literature on round-robin tournament scheduling, whereas the last one, denoted as PartialSwapTeamsPhased, is...

We propose a survey of the research contributions on the field of Educational Timetabling with a specific focus on "standard" formulations and the corresponding benchmark instances. We identify six of such formulations and we discuss their features, pointing out their relevance and usability. Other available formulations and datasets are also revie...

We consider the Minimum Interference Frequency Assignment Problem and we propose a novel Simulated Annealing approach that makes use of a portfolio of different neighborhoods, specifically designed for this problem. We undertake at once the two versions of the problem proposed by Correia (2001) and by Montemanni et al. (2001), respectively, and the...

We propose a Simulated Annealing approach for the Examination Timetabling problem, in the classical uncapacitated formulation of Carter et al. (1996). Our solver is based on a novel combination of many neighborhoods and a principled tuning procedure performed on artificial training instances. The experimental results on real-world benchmarks show t...

In recent years, cold food chains have shown an impressive growth, mainly due to customers life style changes. Consequently, the transportation of refrigerated food is becoming a crucial aspect of the chain, aiming at ensuring efficiency and sustainability of the process while keeping a high level of product quality. The recently defined Refrigerat...

In this work we analyse basketball play-by-play data in order to evaluate the efficiency of different five-man lineups employed by teams. Starting from the adjusted plus-minus framework, we present a model-based strategy for the analysis of the result of partial match outcomes, extending the current literature in two main directions. The first exte...

We investigate the examination timetabling problem in the context of Italian universities. The outcome is the definition of a general problem that can be applied to a large set of universities, but is quite different in many aspects from the classical versions proposed in the literature. We propose both a metaheuristic approach based on Simulated A...

The thesis defense timetabling problem consists in composing the suitable committee for a set of defense sessions and assigning each graduation candidate to one of the sessions. In this work, we define the problem formulation that applies to some Italian universities and we provide three alternative solution methods, based on Integer Programming, C...

We propose a general model for the problem of planning and scheduling steelmaking and casting activities obtained by combining common features and constraints of the operations from a real plant and the literature. For tackling the problem, we develop a simulated annealing approach based on a solution space made of job permutations, which uses as s...

We consider the discrete single-machine, multi-item lot-sizing and scheduling problem and we propose a Simulated Annealing (SA) approach together with a statistically-principled tuning procedure to solve it. We compare our solver with the state-of-the-art methods based on Mixed Integer Programming (MIP), both on publicly-available instances and on...

MiniZinc is a high-level declarative modeling language that has become quite popular in the last few years. One of the main features of MiniZinc is the underlying middle-level constraint language FlatZinc, into which a MiniZinc model, along with a given instance, is translated. In this work, we describe an on-going project consisting in the impleme...

Automation of engineering procedures for the development of new manufacturing processes is of great importance in modern competitive conditions. For example, metalworking companies would greatly benefit from the development of methods for automatic generation, testing and optimization of part programs for machining operations. Indeed, the generatio...

Bike sharing systems need to be properly rebalanced to meet the demand of users and to operate successfully. However, the problem of Balancing Bike Sharing Systems (BBSS) is a demanding task: it requires the design of optimal tours and operating instructions for relocating bikes among stations to maximally comply with the expected future bike deman...

A promising research line in the optimization community regards the hybridization of exact and heuristics methods. In this chapter we survey the specific integration of two complementary optimization paradigms, namely Constraint Programming, for the exact part, and metaheuristics.

We consider the university course timetabling problem, which is one of the most studied problems in educational timetabling. In particular, we focus our attention on the formulation known as curriculum-based course timetabling problem (CB-CTT), which has been tackled by many researchers and has many available benchmarks. The contributions of this p...

We propose an extension of the Generalized Balanced Academic Curriculum Problem (GBACP), a relevant planning problem arising in many universities. The problem consists of assigning courses to teaching terms and years, satisfying a set of precedence constraints and balancing students’ load among terms. Differently from the original GBACP formulation...

Homecare, i.e., supportive care provided at the patients’ homes, is established as a prevalent alternative to unnecessary hospitalization or institutional care (e.g., in a rest home or a nursing home). These activities are provided either by healthcare professional or by non-medical caregivers, depending on the patient’s needs (e.g., medical care o...

In order to meet the users’ demand, bike sharing systems must be regularly rebalanced. The problem of balancing bike sharing systems (BBSS) is concerned with designing optimal tours and operating instructions for relocating bikes among stations to maximally comply with the expected future bike demands. In this paper, we tackle the BBSS by means of...

Balancing bike sharing systems is an increasingly important problem, because of the rising popularity of this mean of transportation. Bike sharing systems need to be balanced so that bikes (and empty slots for returning bikes) are available to the customers, thus ensuring an adequate level of service. In this paper, we tackle the problem of balanci...

This paper is the organizers’ report on the Third International Timetabling Competition (ITC2011), run during 2011–2012 with the aim of raising the profile of automated high school timetabling. Its participants tackled 35 instances of the high school timetabling problem, taken from schools in 10 countries. The paper describes the data model used, t...

We present GELATO, a general tool for encoding and solving optimization problems. Problems can be modeled using several paradigms and/or languages such as: Prolog, MiniZinc, and GECODE. Other paradigms can be included. Solution search is performed by a hybrid solver that exploits the potentiality of the Constraint Programming environment GECODE and...

Shift design and break scheduling are important employee scheduling problems that arise in many contexts, especially at airports, call centers, and service industries. The aim is to find a minimum number of legal shifts, the number of workers assigned to them, and a suitable number of breaks so that the deviation from predetermined workforce requir...

Haplotype Inference is a challenging problem in bioinformatics that consists in inferring the basic genetic constitution of diploid organisms on the basis of their genotypes. This piece of information makes it possible to perform association studies for the genetic variants involved in multifactorial diseases and the individual responses to therape...

We propose a set of formulations for the Curriculum-Based Course Timetabling problem, with the aim of “capturing” many real-world formulations, and thus encouraging researchers to “reduce” their specific problems to one of them, gaining the opportunity to compare and assess their results. This work is accompanied by a web application that maintains...

In our participation to the Cross-Domain Heuristic Search Challenge (CHeSC 2011) [1] we developed an approach based on Reinforcement Learning for the automatic, on-line selection of low-level heuristics across different problem domains. We tested different memory models and learning techniques to improve the results of the algorithm. In this paper...

Portfolio selection is a problem arising in finance and economics. While its basic formulations can be efficiently solved using linear or quadratic programming, its more practical and realistic variants, which include various kinds of constraints and objectives, have in many cases to be tackled by heuristics. In this work, we present a hybrid techn...

The post-enrolment course timetabling (PE-CTT) is one of the most studied timetabling problems, for which many instances and results are available. In this work we design a metaheuristic approach based on Simulated Annealing to solve the PE-CTT. We consider all the different variants of the problem that have been proposed in the literature and we p...

The Balanced Academic Curriculum Problem (BACP) consists in assigning courses to teaching terms satisfying prerequisites and balancing the credit course load within each term. The BACP is part of the CSPLib with three benchmark instances, but its formulation is simpler than the problem solved in practice by universities. In this article, we introdu...

The Portfolio Selection Problem [7] is amongst the most studied issues in finance. In this problem, given a universe of assets (shares, options, bonds, . . . ), we are concerned in finding out a portfolio (i.e., which asset to invest in and by how much) which minimizes the risk while ensuring a given minimum return. In the most common formulation i...

We propose a hybrid local search algorithm for the solution of the Curriculum-Based Course Timetabling Problem and we undertake a systematic statistical study of the relative influence of the relevant features on the performances of the algorithm. In particular, we apply modern statistical techniques for the design and analysis of experiments, such...

Mr. Hamann gave some of the constraints upon the engineer in the automotive industry.

In this work we formalize a new complex variant of the classical vehicle routing problem arising from a real-world application. Our formulation includes a heterogeneous fleet, a multi-day planning horizon, a complex carrier-dependent cost for vehicles, and the possibility of leaving orders unscheduled. For tackling this problem we propose a metaheu...

The problem of designing workforce shifts and break patterns is a relevant employee scheduling problem that arises in many contexts, especially in service industries. The issue is to find a minimum number of shifts, the number of workers assigned to them, and a suitable number of breaks so that the deviation from predetermined workforce requirement...

The typical scenario of a user seeking information on the Web requires significant effort to get the desired information (Web pages, applications, resources, and so on). The user must submit a query to a Web search engine and then check the results to see if they really provide the desired information. Often the user must refine and resubmit the qu...

The 2nd International Timetabling Competition (ITC2007) was announced on the 1st Au-gust 2007. Building on the success of the first, this competition aimed to further develop interest in the area of educational timetabling while providing researchers with models of the problems faced which incorporate an increased number of real world constraints....

Nowadays, the mobile computing paradigm and the widespread diffusion of mobile devices are quickly changing and replacing many common assumptions about software architectures and interaction/communication models. The environment, in particular, or more generally, the so-called user context is claiming a central role in everyday’s use of cellular ph...

In this work we study a hybrid local search algorithm for the solu-tion of timetabling problems, and we undertake a systematic statistical study of the relative influence of the relevant features on the perfor-mances of the algorithm. In particular, we apply statistical methods for the design and analysis of experiments. This work is still ongoing,...

Haplotype Inference is a challenging problem in bioinformatics that consists in inferring the basic genetic constitution of diploid organisms on the basis of their genotype. This information allows researchers to perform association studies for the genetic variants involved in diseases and the individual responses to therapeutic agents. A notable a...

We present a hybrid solver (called \(\mathbb{GELATO}\)) that exploits the potentiality of a Constraint Programming (CP) environment (Gecode) and of a Local Search (LS) framework (EasyLocal + + ). \(\mathbb{GELATO}\) allows to easily develop and use hybrid meta-heuristic combining CP and LS phases (in particular Large Neighborhood Search). We tested...

We present EasyGenetic, a genetic solver based on template metaprogramming, that enables the user to configure the solver by instantiating template parameters. The framework allows to combine flexibility with efficiency. The framework is mainly designed to be applied to problems for which a master-slave solution strategy can be defined.

I will present the Context Aware Browser, a novel paradigm for context-aware access to Web contents with mobile devices. The idea is to allow automatic download of Web pages, and even automatic execution of Web applications, on user's own mobile device. The Web resources are not simply pushed on the mobile device; rather, they are selected on the b...

Haplotype Inference is a challenging problem in bioinformatics that consists in inferring the basic genetic constitution of diploid organisms on the basis of their genotype. This information allows researchers to perform association studies for the genetic variants involved in diseases and the individual responses to therapeutic agents. A notable a...

Haplotype inference is a challenging problem in bioinformatics that consists in inferring the basic genetic constitution of diploid organisms on the basis of their genotype. This piece of information allows researchers to perform association studies for the genetic variants involved in diseases and the individual responses to therapeutic agents. A...

The Balanced Academic Curriculum Problem (BACP) consists in assigning courses to teaching periods satisfying prerequisites and balancing students’ load. BACP is included in CSPlib along with three benchmark instances. However, the BACP formulation in CSPLib is actually simpler than the real problem that, in general, universities have to solve in pr...

Camera placement in 3D scenes is a relevant issue in most D graphics interactive application, such as videogames, data visualization, and virtual tours. Virtual Camera Composition (VCC) consists in automatically positioning a camera in a virtual world, such that the resulting image satisfies a set of visual cinematographic properties [1]. We propos...

Haplotype Inference is a challenging problem in bioinformatics that consists in inferring the basic genetic constitution of diploid organisms on the basis of their genotype. This information enables researchers to perform association studies for the genetic variants involved in diseases and the individual responses to therapeutic agents. A notable...

The Virtual Camera Composition (VCC) problem consists in auto- matically positioning a camera in a virtual world, such that the resulting image satisfies a set of visual cinematographic properties (3). In this paper, we propose an approach to VCC based on Particle Swarm Optimization(5). We show, in re- alistic situations, that our approach outperfo...

Context aware computing is a computational paradigm that has faced a rapid growth in the last few years, especially in the field of mobile devices. One of the promises of context-awareness in this field is the possibility of automatically adapting the functioning mode of mobile devices to the environment and the current situation the user is in, wi...

Haplotype Inference is a challenging problem in bioinformatics that consists in inferring the basic genetic constitution of diploid organisms on the basis of their genotype. This information allows researchers to perform association studies for the genetic variants involved in diseases and the individual responses to therapeutic agents. A notable a...

The min-Shift Design problem (MSD) is an important scheduling problem that needs to be solved in many industrial contexts. The issue is to find a minimum number of shifts and the number of employees to be assigned to these shifts in order to minimize the deviation from workforce requirements. Our research considers both theoretical and practical a...

Portfolio selection is a relevant problem arising in finance and economics. While its basic formulations can be efficiently solved through linear or quadratic programming, its more practical and realistic variants, which include various kinds of constraints and objectives, have in many cases to be tackled by approximate algorithms. In this work, we...

The Traveling Tournament Problem (TTP) is a combinatorial problem that combines features from the traveling salesman problem and the tournament scheduling problem. We propose a family of tabu search solvers for the solution of TTP that make use of complex combination of many neighborhood structures. The different neighborhoods have been thoroughly...

Portfolio selection is a relevant problem arising in nance and economics. While its basic formulation can be ecien tly solved through linear programming, its more practical and realistic variants, that include various kinds of constraints and objec- tives, have to be tackled by approximate algorithms. In this work, we present a hybrid technique tha...

Following the success of the First International Timetabling Competition in 2002, the timetabling research community is organising a new competition on this problem (opening August 1st). This new competition will be on three dierent timetabling problems, and one of the tracks concerns the course timetabling formulation that applies to Italian unive...

One of the aspects of applying software engineering to Stochastic Local Search (SLS) is the principled analysis of the features of the problem instances and the behavior of SLS algorithms, which —because of their stochastic nature— might need sophisticated statistical tools. In this paper we describe EasyAnalyzer, an object-oriented framework for t...

We present a software tool, called EasySyn++, for the automatic synthesis of the source code for a set of stochastic local search (SLS) algorithms. EasySyn++ uses C++ as object language and relies on EasyLocal++, a C++ framework for the development of SLS algorithms. EasySyn++ is particularly suitable for the frequent case of having many neighborho...

EasyLocal++ is an object-oriented framework that helps the user to design and implement local search algorithms in C++ for a large variety of problems. In this paper we highlight the usability of EasyLocal++ by showing its contribution for the development of a solver for a real-life scheduling problem, namely the Course Timetabling problem. The Co...

Most common effectiveness measures for information retrieval systems are based on the assumptions of binary relevance (either a document is relevant to a given query or it is not) and binary retrieval (either a document is retrieved or it is not). In this paper, we describe an information retrieval effectiveness measure named ADM (Average Distance...

Dierent approaches in the hybridization of constraint pro- gramming and local search techniques have been recently proposed in the literature. In this paper we investigate two of them, namely the employment of local search to improve a solution found by constraint programming and the exploitation of a constraint model to perform the exploration of...

In this paper, we first discuss the level of compliance for timetabling research to two important research qualities, namely measurability and reproducibility, analyzing what we believe are the most important contributions in the literature. Secondly, we discuss some practices that, in our opinion, could contribute to the improvement on the two afo...

ADM (Average Distance Measure) is an IR effectiveness metric based on the assumptions of continuous relevance and retrieval. This paper presents some novel experimental results on two different test collections: TREC 8, re-assessed on 4-levels relevance judgments, and TREC 13 TeraByte collection. The results confirm that ADM correlation with standa...

A recent trend in local search concerns the exploitation of several different neighborhoods so as to increase the ability of the algorithm to navigate the search space. In this work we investigate a hybridization technique that we call Neighborhood Portfolio Approach that consists in the interleave of local search techniques based on various combin...

Tabu Search (TS) is a well known local search method which has been widely used for solving AI problems. Different versions of TS have been proposed in the literature, and many features of TS have been considered and tested experimentally. The feature that is present in almost all TS variants is the so called (short-term) tabu list which is recogni...