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Pierre Lopez
Researcher at University of Toulouse
Publications - 105
Citations - 1743
Pierre Lopez is an academic researcher from University of Toulouse. The author has contributed to research in topics: Job shop scheduling & Scheduling (computing). The author has an hindex of 22, co-authored 102 publications receiving 1597 citations. Previous affiliations of Pierre Lopez include Hoffmann-La Roche & Centre national de la recherche scientifique.
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Event-based MILP models for resource-constrained project scheduling problems
TL;DR: A comparative study of several mixed integer linear programming (MILP) formulations for resource-constrained project scheduling problems (RCPSPs) shows that no MILP formulation class dominates the other ones and that a state-of-the art specialized method for the RCPSP is even outperformed by MILP on a set of hard instances.
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A multi-objective local search heuristic for scheduling Earth observations taken by an agile satellite
TL;DR: An indicator-based multi-objective local search (IBMOLS) is presented to solve a multi-Objective optimization problem concerning the selection and scheduling of observations for an agile Earth observing satellite and the results are compared with the biased random-key genetic algorithm.
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The energy scheduling problem: Industrial case-study and constraint propagation techniques
TL;DR: An extension of specific resource constraint propagation techniques to efficiently prune the search space for EnSP solving and a branching scheme to solve the problem via tree search are presented.
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Discrepancy search for the flexible job shop scheduling problem
TL;DR: The results demonstrate that the proposed approach outperforms the best-known algorithms for the FJSP on some types of benchmarks and remains comparable with them on other ones.
Posted Content
Schedule generation schemes for the job-shop problem with sequence-dependent setup times: dominance properties and computational analysis
TL;DR: The proposed S GSs significantly improve previously best-known results on a set of hard benchmark instances and show how the proposed SGSs can be used within single-pass and multi-pass priority rule based heuristics.