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Roberto Tadei

Bio: Roberto Tadei is an academic researcher from Polytechnic University of Turin. The author has contributed to research in topics: Vehicle routing problem & Heuristics. The author has an hindex of 33, co-authored 162 publications receiving 3783 citations. Previous affiliations of Roberto Tadei include Instituto Politécnico Nacional & Telecom Italia.


Papers
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Journal ArticleDOI
TL;DR: Improvements obtained in dealing with job shop scheduling using a heuristic technique based on Genetic Algorithms are presented.

381 citations

Journal ArticleDOI
TL;DR: The family of two-echelon vehicle routing problems (VRPs), a term that broadly covers such settings, where the delivery from one or more depots to customers is managed by routing and consolidating freight through intermediate depots, is introduced.
Abstract: Multiechelon distribution systems are quite common in supply-chain and logistics They are used by public administrations in their transportation and traffic planning strategies, as well as by companies, to model own distribution systems In the literature, most of the studies address issues relating to the movement of flows throughout the system from their origins to their final destinations Another recent trend is to focus on the management of the vehicle fleets required to provide transportation among different echelons The aim of this paper is twofold First, it introduces the family of two-echelon vehicle routing problems (VRPs), a term that broadly covers such settings, where the delivery from one or more depots to customers is managed by routing and consolidating freight through intermediate depots Second, it considers in detail the basic version of two-echelon VRPs, the two-echelon capacitated VRP, which is an extension of the classical VRP in which the delivery is compulsorily delivered through intermediate depots, named satellites A mathematical model for two-echelon capacitated VRP, some valid inequalities, and two math-heuristics based on the model are presented Computational results of up to 50 customers and four satellites show the effectiveness of the methods developed

335 citations

Journal ArticleDOI
TL;DR: The extreme point concept is introduced and a new extreme point-based rule for packing items inside a three-dimensional container is presented, independent from the particular packing problem addressed and can handle additional constraints, such as fixing the position of the items.
Abstract: One of the main issues in addressing three-dimensional packing problems is finding an efficient and accurate definition of the points at which to place the items inside the bins, because the performance of exact and heuristic solution methods is actually strongly influenced by the choice of a placement rule. We introduce the extreme point concept and present a new extreme point-based rule for packing items inside a three-dimensional container. The extreme point rule is independent from the particular packing problem addressed and can handle additional constraints, such as fixing the position of the items. The new extreme point rule is also used to derive new constructive heuristics for the three-dimensional bin-packing problem. Extensive computational results show the effectiveness of the new heuristics compared to state-of-the-art results. Moreover, the same heuristics, when applied to the two-dimensional bin-packing problem, outperform those specifically designed for the problem.

191 citations

Journal ArticleDOI
TL;DR: This paper presents the results of a broad experimental study aimed at analyzing the impact on the total distribution cost of several parameters including customer distribution, satellites-location rules, depot location, number of satellites, mean accessibility of the satellites, and mean transportation cost between the satellites and the customers.

163 citations

Journal ArticleDOI
TL;DR: In this article, the authors studied the problem of minimizing total completion time in a two-machine flow shop and proposed a branch and bound method to minimize the total time in the flow shop.

130 citations


Cited by
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Book
29 Apr 2003
TL;DR: This book provides a self-contained, comprehensive and up-to-date presentation of uncertain programming theory, including numerous modeling ideas, hybrid intelligent algorithms, and applications in system reliability design, project scheduling problem, vehicle routing problem, facility location problem, and machine scheduling problem.
Abstract: Real-life decisions are usually made in the state of uncertainty such as randomness and fuzziness. How do we model optimization problems in uncertain environments? How do we solve these models? In order to answer these questions, this book provides a self-contained, comprehensive and up-to-date presentation of uncertain programming theory, including numerous modeling ideas, hybrid intelligent algorithms, and applications in system reliability design, project scheduling problem, vehicle routing problem, facility location problem, and machine scheduling problem. Researchers, practitioners and students in operations research, management science, information science, system science, and engineering will find this work a stimulating and useful reference.

1,352 citations

Book ChapterDOI
TL;DR: A survey of results concerning algorithms, complexity, and applications of the maximum clique problem is presented and enumerative and exact algorithms, heuristics, and a variety of other proposed methods are discussed.
Abstract: The maximum clique problem is a classical problem in combinatorial optimization which finds important applications in different domains. In this paper we try to give a survey of results concerning algorithms, complexity, and applications of this problem, and also provide an updated bibliography. Of course, we build upon precursory works with similar goals [39, 232, 266].

1,065 citations

Journal ArticleDOI
TL;DR: This work deals with the biological inspiration of ant colony optimization algorithms and shows how this biological inspiration can be transfered into an algorithm for discrete optimization, and presents some of the nowadays best-performing ant colonies optimization variants.

1,041 citations

01 Dec 1971

979 citations

Journal ArticleDOI
TL;DR: A review of the literature on stochastic and robust facility location models can be found in this article, where the authors illustrate both the rich variety of approaches for optimization under uncertainty and their application to facility location problems.
Abstract: Plants, distribution centers, and other facilities generally function for years or decades, during which time the environment in which they operate may change substantially. Costs, demands, travel times, and other inputs to classical facility location models may be highly uncertain. This has made the development of models for facility location under uncertainty a high priority for researchers in both the logistics and stochastic/robust optimization communities. Indeed, a large number of the approaches that have been proposed for optimization under uncertainty have been applied to facility location problems. This paper reviews the literature on stochastic and robust facility location models. Our intent is to illustrate both the rich variety of approaches for optimization under uncertainty that have appeared in the literature and their application to facility location problems. In a few instances for which examples in facility location are not available, we provide examples from the more general logistics l...

970 citations