Solving a job shop scheduling problem on the line of treatment surface and automation of production system
type: Dataset
description: In this thesis we study the automated electroplating lines. In these lines, the products are immerged in different tanks. The processing times are bounded. The lower bound represents the minimum time to treat the product while the upper bound depends on the treatment.A classical objective is to ﬁnd the robot moves which minimize the cycle time, this is called ”hoist scheduling problem” (HSP). In this thesis, we study particularly the single-hoist/multi-products.In this direction, three approaches are presented to solve the single-hoist/multi-products problem with introducing the hoist moves time: constraints satisfaction algorithm based on non standard criteria witch the hoist wait time, hybridization with classical heuristics improving the obtained results, and finally the genetic algorithm to optimize the cycle time. Robustness’ notions are finally exploited in the presence of a disturbance at the critical resource of the workshop which is the hoist.The systematic determination of a robust scheduling has been conducted successfully introducing new performance indicators and by applying a multicriteria evaluation method
landing page: https://theses.hal.science/tel-00992026
identifier: NNT: 2011ECLI0004
keyword: algorithme-de-satisfaction-de-contraintes
keyword: algorithmes-genetiques
keyword: constraints-satisfaction-algorithm
keyword: genetic-algorithm
keyword: hybridation
keyword: infoeu-reposemanticsdoctoralthesis
keyword: metaheuristics
keyword: metaheuristiques
keyword: optimisation
keyword: optimization
keyword: ordonnancement
keyword: scheduling
keyword: spiotherengineering-sciences-physicsother
keyword: theses
issued: 2026-05-05T11:03:50.081412
modified: 2026-05-05T11:03:50.081416
language: fr
contact point: Organization
  fn: CCSD

test_moissonnage_selune
type: Agent

Solving a job shop scheduling problem on the line of treatment surface and automation of production system
type: Distribution
format: HTML
access URL: https://theses.hal.science/tel-00992026
issued: 2026-05-05T11:03:50.085095
modified: 2026-05-05T11:03:50.063683