Essays in structural heuristics

This dissertation introduces and develops a new method of rational reconstruction called structural heuristics. Structural heuristics takes assignment of structure to any given object of investigation as the starting point for its rational reconstruction. This means to look at any given object as a system of relations and of transformation laws for those relations. The operational content of this heuristics can be summarized as follows: when facing any given system the best way to approach it is to explicitly look for a possible structure of it. The utilization of structural heuristics allows structural awareness, which is considered a fundamental epistemic disposition, as well as a fundamental condition for the rational reconstruction of systems of knowledge. In this dissertation, structural heuristics is applied to reconstructing the domain of economic knowledge. This is done by exploring four distinct areas of economic research: (i) economic axiomatics; (ii) realism in economics; (iii) production theory; (iv) economic psychology. The application of structural heuristics to these fields of economic inquiry shows the flexibility and potential of structural heuristics as epistemic tool for theoretical exploration and reconstruction.

Algorithms for network design and routing problems

In this thesis we study three combinatorial optimization problems belonging to the classes of Network Design and Vehicle Routing problems that are strongly linked in the context of the design and management of transportation networks: the Non-Bifurcated Capacitated Network Design Problem (NBP), the Period Vehicle Routing Problem (PVRP) and the Pickup and Delivery Problem with Time Windows (PDPTW). These problems are NP-hard and contain as special cases some well known difficult problems such as the Traveling Salesman Problem and the Steiner Tree Problem. Moreover, they model the core structure of many practical problems arising in logistics and telecommunications. The NBP is the problem of designing the optimum network to satisfy a given set of traffic demands. Given a set of nodes, a set of potential links and a set of point-to-point demands called commodities, the objective is to select the links to install and dimension their capacities so that all the demands can be routed between their respective endpoints, and the sum of link fixed costs and commodity routing costs is minimized. The problem is called non- bifurcated because the solution network must allow each demand to follow a single path, i.e., the flow of each demand cannot be splitted. Although this is the case in many real applications, the NBP has received significantly less attention in the literature than other capacitated network design problems that allow bifurcation. We describe an exact algorithm for the NBP that is based on solving by an integer programming solver a formulation of the problem strengthened by simple valid inequalities and four new heuristic algorithms. One of these heuristics is an adaptive memory metaheuristic, based on partial enumeration, that could be applied to a wider class of structured combinatorial optimization problems. In the PVRP a fleet of vehicles of identical capacity must be used to service a set of customers over a planning period of several days. Each customer specifies a service frequency, a set of allowable day-combinations and a quantity of product that the customer must receive every time he is visited. For example, a customer may require to be visited twice during a 5-day period imposing that these visits take place on Monday-Thursday or Monday-Friday or Tuesday-Friday. The problem consists in simultaneously assigning a day- combination to each customer and in designing the vehicle routes for each day so that each customer is visited the required number of times, the number of routes on each day does not exceed the number of vehicles available, and the total cost of the routes over the period is minimized. We also consider a tactical variant of this problem, called Tactical Planning Vehicle Routing Problem, where customers require to be visited on a specific day of the period but a penalty cost, called service cost, can be paid to postpone the visit to a later day than that required. At our knowledge all the algorithms proposed in the literature for the PVRP are heuristics. In this thesis we present for the first time an exact algorithm for the PVRP that is based on different relaxations of a set partitioning-like formulation. The effectiveness of the proposed algorithm is tested on a set of instances from the literature and on a new set of instances. Finally, the PDPTW is to service a set of transportation requests using a fleet of identical vehicles of limited capacity located at a central depot. Each request specifies a pickup location and a delivery location and requires that a given quantity of load is transported from the pickup location to the delivery location. Moreover, each location can be visited only within an associated time window. Each vehicle can perform at most one route and the problem is to satisfy all the requests using the available vehicles so that each request is serviced by a single vehicle, the load on each vehicle does not exceed the capacity, and all locations are visited according to their time window. We formulate the PDPTW as a set partitioning-like problem with additional cuts and we propose an exact algorithm based on different relaxations of the mathematical formulation and a branch-and-cut-and-price algorithm. The new algorithm is tested on two classes of problems from the literature and compared with a recent branch-and-cut-and-price algorithm from the literature.

Algorithms for UAS insertion in civil air space

One of the most interesting challenge of the next years will be the Air Space Systems automation. This process will involve different aspects as the Air Traffic Management, the Aircrafts and Airport Operations and the Guidance and Navigation Systems. The use of UAS (Uninhabited Aerial System) for civil mission will be one of the most important steps in this automation process. In civil air space, Air Traffic Controllers (ATC) manage the air traffic ensuring that a minimum separation between the controlled aircrafts is always provided. For this purpose ATCs use several operative avoidance techniques like holding patterns or rerouting. The use of UAS in these context will require the definition of strategies for a common management of piloted and piloted air traffic that allow the UAS to self separate. As a first employment in civil air space we consider a UAS surveillance mission that consists in departing from a ground base, taking pictures over a set of mission targets and coming back to the same ground base. During all mission a set of piloted aircrafts fly in the same airspace and thus the UAS has to self separate using the ATC avoidance as anticipated. We consider two objective, the first consists in the minimization of the air traffic impact over the mission, the second consists in the minimization of the impact of the mission over the air traffic. A particular version of the well known Travelling Salesman Problem (TSP) called Time-Dependant-TSP has been studied to deal with traffic problems in big urban areas. Its basic idea consists in a cost of the route between two clients depending on the period of the day in which it is crossed. Our thesis supports that such idea can be applied to the air traffic too using a convenient time horizon compatible with aircrafts operations. The cost of a UAS sub-route will depend on the air traffic that it will meet starting such route in a specific moment and consequently on the avoidance maneuver that it will use to avoid that conflict. The conflict avoidance is a topic that has been hardly developed in past years using different approaches. In this thesis we purpose a new approach based on the use of ATC operative techniques that makes it possible both to model the UAS problem using a TDTSP framework both to use an Air Traffic Management perspective. Starting from this kind of mission, the problem of the UAS insertion in civil air space is formalized as the UAS Routing Problem (URP). For this reason we introduce a new structure called Conflict Graph that makes it possible to model the avoidance maneuvers and to define the arc cost function of the departing time. Two Integer Linear Programming formulations of the problem are proposed. The first is based on a TDTSP formulation that, unfortunately, is weaker then the TSP formulation. Thus a new formulation based on a TSP variation that uses specific penalty to model the holdings is proposed. Different algorithms are presented: exact algorithms, simple heuristics used as Upper Bounds on the number of time steps used, and metaheuristic algorithms as Genetic Algorithm and Simulated Annealing. Finally an air traffic scenario has been simulated using real air traffic data in order to test our algorithms. Graphic Tools have been used to represent the Milano Linate air space and its air traffic during different days. Such data have been provided by ENAV S.p.A (Italian Agency for Air Navigation Services).

Reexamining the Role of Incarceration and Stigma in Criminal Law

One of the ways by which the legal system has responded to different sets of problems is the blurring of the traditional boundaries of criminal law, both procedural and substantive. This study aims to explore under what conditions does this trend lead to the improvement of society's welfare by focusing on two distinguishing sanctions in criminal law, incarceration and social stigma. In analyzing how incarceration affects the incentive to an individual to violate a legal standard, we considered the crucial role of the time constraint. This aspect has not been fully explored in the literature on law and economics, especially with respect to the analysis of the beneficiality of imposing either a fine or a prison term. We observed that that when individuals are heterogeneous with respect to wealth and wage income, and when the level of activity can be considered a normal good, only the middle wage and middle income groups can be adequately deterred by a fixed fines alone regime. The existing literature only considers the case of the very poor, deemed as judgment proof. However, since imprisonment is a socially costly way to deprive individuals of their time, other alternatives may be sought such as the imposition of discriminatory monetary fine, partial incapacitation and other alternative sanctions. According to traditional legal theory, the reason why criminal law is obeyed is not mainly due to the monetary sanctions but to the stigma arising from the community’s moral condemnation that accompanies conviction or merely suspicion. However, it is not sufficiently clear whether social stigma always accompanies a criminal conviction. We addressed this issue by identifying the circumstances wherein a criminal conviction carries an additional social stigma. Our results show that social stigma is seen to accompany a conviction under the following conditions: first, when the law coincides with the society's social norms; and second, when the prohibited act provides information on an unobservable attribute or trait of an individual -- crucial in establishing or maintaining social relationships beyond mere economic relationships. Thus, even if the social planner does not impose the social sanction directly, the impact of social stigma can still be influenced by the probability of conviction and the level of the monetary fine imposed as well as the varying degree of correlation between the legal standard violated and the social traits or attributes of the individual. In this respect, criminal law serves as an institution that facilitates cognitive efficiency in the process of imposing the social sanction to the extent that the rest of society is boundedly rational and use judgment heuristics. Paradoxically, using criminal law in order to invoke stigma for the violation of a legal standard may also serve to undermine its strength. To sum, the results of our analysis reveal that the scope of criminal law is narrow both for the purposes of deterrence and cognitive efficiency. While there are certain conditions where the enforcement of criminal law may lead to an increase in social welfare, particularly with respect to incarceration and stigma, we have also identified the channels through which they could affect behavior. Since such mechanisms can be replicated in less costly ways, society should first try or seek to employ these legal institutions before turning to criminal law as a last resort.

Lifelines in case of Natural Disaster Emergencies

In order to handle Natural disasters, emergency areas are often individuated over the territory, close to populated centres. In these areas, rescue services are located which respond with resources and materials for population relief. A method of automatic positioning of these centres in case of a flood or an earthquake is presented. The positioning procedure consists of two distinct parts developed by the research group of Prof Michael G. H. Bell of Imperial College, London, refined and applied to real cases at the University of Bologna under the coordination of Prof Ezio Todini. There are certain requirements that need to be observed such as the maximum number of rescue points as well as the number of people involved. Initially, the candidate points are decided according to the ones proposed by the local civil protection services. We then calculate all possible routes from each candidate rescue point to all other points, generally using the concept of the "hyperpath", namely a set of paths each one of which may be optimal. The attributes of the road network are of fundamental importance, both for the calculation of the ideal distance and eventual delays due to the event measured in travel time units. In a second phase, the distances are used to decide the optimum rescue point positions using heuristics. This second part functions by "elimination". In the beginning, all points are considered rescue centres. During every interaction we wish to delete one point and calculate the impact it creates. In each case, we delete the point that creates less impact until we reach the number of rescue centres we wish to keep.

Social learning and action understanding in human observers: contributions of sensori-motor constraints and prior information

The aim of this thesis was to investigate the respective contribution of prior information and sensorimotor constraints to action understanding, and to estimate their consequences on the evolution of human social learning. Even though a huge amount of literature is dedicated to the study of action understanding and its role in social learning, these issues are still largely debated. Here, I critically describe two main perspectives. The first perspective interprets faithful social learning as an outcome of a fine-grained representation of others’ actions and intentions that requires sophisticated socio-cognitive skills. In contrast, the second perspective highlights the role of simpler decision heuristics, the recruitment of which is determined by individual and ecological constraints. The present thesis aims to show, through four experimental works, that these two contributions are not mutually exclusive. A first study investigates the role of the inferior frontal cortex (IFC), the anterior intraparietal area (AIP) and the primary somatosensory cortex (S1) in the recognition of other people’s actions, using a transcranial magnetic stimulation adaptation paradigm (TMSA). The second work studies whether, and how, higher-order and lower-order prior information (acquired from the probabilistic sampling of past events vs. derived from an estimation of biomechanical constraints of observed actions) interacts during the prediction of other people’s intentions. Using a single-pulse TMS procedure, the third study investigates whether the interaction between these two classes of priors modulates the motor system activity. The fourth study tests the extent to which behavioral and ecological constraints influence the emergence of faithful social learning strategies at a population level. The collected data contribute to elucidate how higher-order and lower-order prior expectations interact during action prediction, and clarify the neural mechanisms underlying such interaction. Finally, these works provide/open promising perspectives for a better understanding of social learning, with possible extensions to animal models.

Heuristic algorithms for the Capacitated Location-Routing Problem and the Multi-Depot Vehicle Routing Problem

The Capacitated Location-Routing Problem (CLRP) is a NP-hard problem since it generalizes two well known NP-hard problems: the Capacitated Facility Location Problem (CFLP) and the Capacitated Vehicle Routing Problem (CVRP). The Multi-Depot Vehicle Routing Problem (MDVRP) is known to be a NP-hard since it is a generalization of the well known Vehicle Routing Problem (VRP), arising with one depot. This thesis addresses heuristics algorithms based on the well-know granular search idea introduced by Toth and Vigo (2003) to solve the CLRP and the MDVRP. Extensive computational experiments on benchmark instances for both problems have been performed to determine the effectiveness of the proposed algorithms. This work is organized as follows: Chapter 1 describes a detailed overview and a methodological review of the literature for the the Capacitated Location-Routing Problem (CLRP) and the Multi-Depot Vehicle Routing Problem (MDVRP). Chapter 2 describes a two-phase hybrid heuristic algorithm to solve the CLRP. Chapter 3 shows a computational comparison of heuristic algorithms for the CLRP. Chapter 4 presents a hybrid granular tabu search approach for solving the MDVRP.

Assessing Household Food Waste in Italy: A Methodology for Detecting Drivers and Quantities

It has been estimated that one third of edible food destined for human consumption is lost or wasted along the food supply chain globally. Much of the waste comes from Global North, where consumers are considered as the bigger contributors. Different studies tried to analyze and estimate the Household Food Waste (HFW), especially in UK and Northern Europe. The result is that accurate studies at national level exist only in UK, Finland and Norway while no such studies are available in Italy, except for survey- based researches. Though, there is a widespread awareness that such methods might be not able to estimate Food Waste. Results emerging from literature clearly suggest that survey estimate inferior amounts of Food Waste as a result, if compared to waste sorting and weighting analysis or to diary studies. The hypothesis that household food waste is under-estimated when gathered through questionnaires has been enquired into. First, a literature review of behavioral economics and heuristics has been proposed; then, a literature review of the sector listing the existing methodologies to gather national data on Household Food Waste has been illustrated. Finally, a pilot experiment to test a mixed methodology is proposed. While literature suggests that four specific cognitive biases might be able to affect the reliability of answers in questionnaires, results of the present experiment clearly indicate that there is a relevant difference between how much the individual thinks to waste and he/she actually does. The result is a mixed methodology based on questionnaire, diary and waste sorting, able to overcome the cons of each single method.