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Davide Anghinolfi

Researcher at University of Genoa

Publications -  45
Citations -  1094

Davide Anghinolfi is an academic researcher from University of Genoa. The author has contributed to research in topics: Ant colony optimization algorithms & Metaheuristic. The author has an hindex of 15, co-authored 45 publications receiving 974 citations.

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Journal ArticleDOI

Energy-aware scheduling for improving manufacturing process sustainability: A mathematical model for flexible flow shops

TL;DR: In this paper, a mixed integer programming (MIP) model is used for energy-aware scheduling of manufacturing processes, where the reference schedule is modified to account for energy consumption.
Journal ArticleDOI

A new discrete particle swarm optimization approach for the single-machine total weighted tardiness scheduling problem with sequence-dependent setup times

TL;DR: A new Discrete Particle Swarm Optimization approach to face the NP-hard single machine total weighted tardiness scheduling problem in presence of sequence-dependent setup times using a discrete model both for particle position and velocity and a coherent sequence metric.
Journal ArticleDOI

A dynamic optimization model for solid waste recycling.

TL;DR: From optimal results, it has been found that the net benefits of the optimized collection are about 2.5 times greater than the estimated current policy.
Journal ArticleDOI

Parallel machine total tardiness scheduling with a new hybrid metaheuristic approach

TL;DR: Evaluating the possibility of defining a hybrid customizable neighbourhood search algorithm for combinatorial problems as a combination of a subset of concepts and features from three main metaheuristics of reference, i.e., the TS, the SA and the VNS aims to evaluate the effectiveness of the HMH.
Book ChapterDOI

An experimental comparison of different heuristics for the master bay plan problem

TL;DR: Two new solution procedures are proposed in this paper: a fast simple constructive loading heuristic (LH) and an ant colony optimization (ACO) algorithm.