1,721,000 research outputs found
The capacitated transshipment problem under uncertainty. CIRRELT- 2009-38
No full textSottomesso a Mathematical Programmin
LSTM Noise Robustness: A Case Study for Heavy Vehicles
No full textArtificial intelligence (AI) techniques are becoming more and more widespread. This is directly related to technology progress and aspects as the flexibility and adaptability of the algorithms considered, key characteristics that allow their use in the most variegated fields. Precisely the increasing diffusion of these techniques leads to the necessity of evaluating their robustness and reliability. This field is still quite unexplored, especially considering the automotive sector, where the algorithms need to be prepared to answer noise problems in data acquisition. For this reason, a methodology directly linked to previous works in the heavy vehicles field is presented. In particular, the same is focused on the estimation of rollover indexes, one of the main issues in road safety scenarios. The purpose is to expand the cited works, addressing the LSTM networks performance in case of strongly disturbed signals
The stochastic generalized bin packing problem
No full textThe Generalized Bin Packing Problem (GBPP) is a recently introduced packing problem where, given a set of bins characterized by volume and cost and a set of items characterized by volume and profit (which also depends on bins), we want to select a subset of items to be loaded into a subset of bins which maximizes the total net profit, while satisfying the volume and bin availability constraints. The total net profit is given by the difference between the total profit of the loaded items and the total cost of the used bins. In this paper, we consider the stochastic version of the GBPP (S-GBPP), where the item profits are random variables to take into account the profit oscillations due to the handling operations for bin loading. The probability distribution of these random variables is assumed to be unknown. By using the asymptotic theory of extreme values a deterministic approximation for the S-GBPP is derived. © 2011 Elsevier B.V. All rights reserved
A Generalized Bin Packing Problem for parcel delivery in last-mile logistics
No full textIn this paper, we present a new problem arising at a tactical level of setting a last-mile parcel delivery service in a city by considering different Transportation Companies (TC), which differ in cost and service quality. The courier must decide which TCs to select for the service in order to minimize the total cost and maximize the total service quality. We show that the problem can be modeled as a new packing problem, the Generalized Bin Packing Problem with bin-dependent item profits (GBPPI), where the items are the parcels to deliver and the bins are the TCs. The aim of the GBPPI is to select the appropriate fleet from TCs and determine the optimal assignment of parcels to vehicles such that the overall net cost is minimized. This cost takes into account both transportation costs and service quality. We provide a Mixed Integer Programming formulation of the problem, which is the starting point for the development of efficient heuristics that can address the GBPPI for instances involving up to 1000 items. Extensive computational tests show the accuracy of the proposed methods. Finally, we present a last-mile logistics case study of an international courier which addresses this problem
Innovative Business Models in Ports' Logistics
No full textSince the global request for freight transportation is increasing as a consequence of the increasing requirements of the modern economy, logistics processes need to be optimized through the application of innovative technologies, to ensure a high level of quality, flexibility, and effectiveness in logistics operations. The adoption of innovative technologies allows the creation and development of new products and services, able to optimize the existing logistics processes and create value. In particular, one of the most promising technology for logistics applications is the 5G communication network that allows, together with companion technologies such as the Internet of Things, Artificial Intelligence, and the Cloud, the collection, integration, and sharing of a large amount of data from different sources. However, to ensure the market adoption of innovative products and services, the different actors and stakeholders of the logistics chain must be involved from the early stages of the development. This allows them to keep into account their actual needs in the development process of the business models and for the future exploitation of the solutions. This paper analyzes the process of development of collaborative business models in the context of 5G-LOGINNOV, a project aimed at the development of 5G-based solutions to optimize the logistics operations in ports and retro-ports
The capacitated transshipment location problem with stochastic handling utilities at the facilities
No full textThe problem consists in finding a transshipment facilities location that maximizes the total net utility when the handling utilities at the facilities are stochastic variables, under supply, demand, and lower and upper capacity constraints. The total net utility is given by the expected total shipping utility minus the total fixed cost of the located facilities. Shipping utilities are given by a deterministic utility for shipping freight from origins to destinations via transshipment facilities plus a stochastic handling utility at the facilities, whose probability distribution is unknown. After giving the stochastic model, by means of some results of the extreme values theory, the probability distribution of the maximum stochastic utilities is derived and the expected value of the optimum of the stochastic model is found. An efficient heuristics for solving real-life instances is also given. Computational results show a very good performance of the proposed methods both in terms of accuracy and efficiency. © 2012 International Federation of Operational Research Societies
Sustainable mobility and user preferences by crowdsourcing data: the Open Agora project
No full textOne application of network optimization is the study of the policies able to change people habits in transportation mode selection. The main strategy for achieving this objective is to develop a model describing the preferences of the people by considering the characteristics of the transportation modes (such as cost, travel duration) and then to develop policies in order to improve the characteristics of the target transportation mode. These models are called utility models and have a long story. Nevertheless, the data needed for their fitting are difficult to get. One of the main issues in this case is how to collect the data and how to tune a model that can be easily scaled and adapted to different settings. In this paper, we describe the results achieved during the Open Agora project where the utility model is tined with crowdsourcing data coming from mobile phone applications and collected indirectly by the users
The multi-path Traveling Salesman Problem with stochastic travel costs
Full text linkGiven a set of nodes, where each pair of nodes is connected by several paths and each path shows a stochastic travel cost with unknown probability distribution, the multi-path Traveling Salesman Problem with stochastic travel costs aims at finding an expected minimum Hamiltonian tour connecting all nodes. Under a mild assumption on the unknown probability distribution, a deterministic approximation of the stochastic problem is given. The comparison of such approximation with a Monte Carlo simulation shows both the accuracy and the efficiency of the deterministic approximation, with a mean percentage gap around 2% and a reduction of the computational times of two orders of magnitude
- …
