A novel Dynamic programming approach for Two-Echelon Capacitated Vehicle Routing Problem in City Logistics with Environmental considerations

Abstract The paper proposes a Two-Echelon Capacitated Vehicle Routing Problem with Environmental consideration, intended for managing urban freight distribution in City Logistics. It presents a novel Dynamic programming approach that divides the main problem into several ones and uses an exact algorithm to obtain optimal route paths. The approach applies Fuzzy C-Means Clustering for assigning a group of customers to a satellite. The initial solution is improved with roulette selection, 2-opt, and Or-opt exchange heuristics. The approach was tested on benchmark instances, and obtained results are satisfactory. Moreover, the proposed method highlights the environmental improvement we can obtain in managing urban freight transportation

A community of agents as a tool to optimize industrial districts logistics

The aim of this paper is to find an optimal solution to operational planning of freight transportation in an industrial district. We propose a system architecture that drives agents – the industrial district firms - to cooperate in logistic field, to minimize transport and environmental costs. The idea is to achieve logistics optimization setting up a community made of district enterprises, preserving a satisfactory level of system efficiency and fairness. We address the situation in which a virtual coordinator helps the agents to reach an agreement. The objectives are: maximizing customers satisfaction, and minimizing the number of trucks needed. A fuzzy clustering (FCM), two Fuzzy Inference System (FIS) combined with a Genetic Algorithm (GA), and a greedy algorithm are thus proposed to achieve these objectives, and eventually an algorithm to solve the Travelling Salesman Problem is also used. The proposed framework can be used to provide real time solutions to logistics management problems, and negative environmental impacts

A Fuzzy set-based method to identify the car position in a road lane at intersections by smartphone GPS data

Abstract Intelligent transportation systems (ITS) work by collections of data in real time. Average speed, travel time and delay at intersections are some of the most important measures, often used for monitoring the performance of transportation systems, and useful for system management and planning. In urban transportation planning, intersections are usually considered critical points, acting as bottlenecks and clog points for urban traffic. Thus, detecting the travel time at intersections in different turning directions is an activity useful to improve the urban transport efficiency. Smartphones represent a low-cost technology, with which is possible to obtain information about traffic state. However, smartphone GPS data suffer for low precision, mainly in urban areas. In this paper, we present a fuzzy set-based method for car positioning identification within road lanes near intersections using GPS data coming from smartphones. We have introduced the fuzzy sets to take into account uncertainty embedded in GPS data when trying to identify the position of cars within the road lanes. Moreover, we introduced a Genetic Algorithm to calibrate the fuzzy parameters in order to obtain a novel supervised clustering technique. We applied the proposed method to one intersection in the urban road network of Bari (Italy). First results reveal the effectiveness of the proposed methodology when comparing the outcomes of the proposed method with two well-known clustering techniques (Fuzzy C-means, K-means)

The Centrencephalic Space of Functional Integration: a Model for Complex Intelligent Systems

If we have recently begun to understand how DNA gives life to embryos and then to individuals, only very little is understood of the intricate interactions between the biological bases of life, the environment and the human brain. The exponential acceleration of technological change could change many, perhaps all, the rules that have guided our civilization so far. It is very likely that these intelligent artificial entities will take much less time to understand the codes that constitute them, gaining forms of (self) awareness, decision-making skills, introspective capacities, mind reading and even free will. If all this is achieved, in the coming decades humanity will be destined to a profound cultural, epistemological and even physiological transformation. In this paper, we aim to show how the success or failure of a balanced man-machine co-evolution will also depend on some answers to fundamental scientific questions that have remained unexplored, such as consciousness and decision-making, creativity, but above all to the adaptive factor that more radically sustained and pushed the evolution beyond the constraints of our genetic code: improvisation. This entanglement of neuronal matrices could be at the origin of an intermodal communication — consists of a stream of semantic phenomena, mental images and more, tuned thanks to “pattern recognition” in centrencephalic space of functional integration — thus explaining “remote spectrum actions” at the base of primary adaptive unconscious and experiences life

Revision on psychometric properties of the temperament and character inventory in a clinical sample

Cloninger’s Temperament and Character Inventory (TCI) although elaborated on the general population, is frequently used in clinical samples. The study evaluates the psychometric characteristics of TCI in clinical populations with the aim of creating a reduced version of the test suitable for these subjects. This research was conducted on two groups of mental health outpatients. In the first study, 44 items, correlated with the psychiatric disorders, was selected. These items, divided in four dimensions utilizing both statistic and psychopathological criteria, show good internal consistency and external validity and constitute a Reduced Version (TR-TCI) of the test. In the second study, the predictive validity of the TR-TCI was evaluated through the ROC curves and a logistic regression model. The results show a good predictive validity of TR-TCI, that allows us to use this instrument in order to identify the personality structures that make people sensitive to psychiatric pathologies

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Criatividade, pesquisa e inovação. O caminho surprendente da descoberta

The semantic horizon of the term innovation is fairly broad, at least as broad as the mental processes that are at its origin and the changes it engenders. Through ever new combinations of ideas and events, innovation brings about changes and discontinuity in scientific, cultural, and social paradigms. Above all, innovation is the ability of the mind to combine ludic and logic elements, extract from apparently banal data new and surprising elements, provide divergent and creative responses, and generate different hypotheses, scenarios, and solutions in almost casual fashion – even outside a structured logic