Proposition of New Genetic Operator for Solving Joint Production and Maintenance Scheduling : Application to the Flow Shop Problem.

International audienceGenetic algorithms are used in scheduling leading to efficient heuristic methods for large sized problems. The efficiency of a GA based heuristic is closely related to the quality of the used GA scheme and the GA operators: mutation, selection and crossover. In this paper, we propose a Joint Genetic Algorithm (JGA), for joint production and maintenance scheduling problem in permutation flowshop, in which different genetic joint operators are used. We also proposed a joint structure to represent an individual in with two fields: the first one for production data and the second one for maintenance data. We used different Taillard benchmarks to compare the performances of JGA with each proposed operator

An integrated ACO approach for the joint production and preventive maintenance scheduling problem in the flowshop sequencing problem.

International audienceIn this paper, an integrated ACO approach to solve joint production and preventive maintenance scheduling problem in permutation flowshops is considered. A newly developed antcolony algorithm is proposed and analyzed for solving this problem, based on a common representation of production and maintenance data, to obtain a joint schedule that is, subsequently, improved by a new local search procedure. The goal is to optimize a common objective function which takes into account both maintenance and production criteria. We compare the results obtained with our algorithm to those of an integrated genetic algorithm developed in previous works. The results and experiments carried out indicate that the proposed ant-colony algorithm provide very effective solutions for this problem

A study of maintenance contribution to joint production and preventive maintenance scheduling problems in the robustness framework.

International audienceIn this paper, we deal with a joint production and Preventive Maintenance (PM) scheduling problem in the robustness framework. The contributions of this paper are twofold. First, we will establish that the insertion of maintenance activities during production scheduling can hedge against some changes in the shop environment. Furthermore, we will check if respecting the optimal intervals of maintenance activities guarantees a minimal robustness threshold. Then, we will try to identify from the used optimisation criteria those that allow making predictive schedules more robust. The computational experiments in a flowshop show that joint production and PM schedules are more robust than production schedules and maintenance provides an acceptable tradeoff between equipment reliability and performance loss under disruption

Joint scheduling of jobs and preventive maintenance operations in the flowshop sequencing problem: A resolution with sequential and integrated strategies.

International audienceUsually, scheduling of maintenance operations and production sequencing are dealt with separately in the literature and, therefore, also in the industry. Given that maintenance affects available production time and elapsed production time affects the probability of machine failure, this interdependency seems to be overlooked in the literature. This paper presents a comparative study on joint production and preventive maintenance scheduling strategies regarding flowshop problems. The sequential strategy which consists of two steps: first scheduling the production jobs then inserting maintenance operations, taking the production schedule as a strong constraint. The integrated one which consists of simultaneously scheduling both maintenance and production activities based on a common representation of these two activities. For each strategy, a constructive heuristic and two meta-heuristics are proposed: NEH heuristic, Genetic algorithm and Taboo search. The goal is to optimize an objective function which takes into account both production and maintenance criteria. The proposed heuristics have been applied to non-standard test problems which represent joint production and maintenance benchmark flowshop scheduling problems taken from Benbouzid et al. (2003). A comparison of the solutions yielded by the heuristics developed in this paper with the heuristic solutions given by Taillard (1993) is undertaken with respect to the minimization of performance loss after maintenance insertion. The comparison shows that the proposed integrated GAs are clearly superior to all the analyzed algorithms

Contribution à l'étude de la performance et de la robustesse des ordonnancements conjoints Production/Maintenance - Cas du Flowshop.

Maintenance and the production are two functions which act on the same resources. However the scheduling of their respective activities is independent, and does not take into account this constraint. The resources (machines) are always regarded as being constantly or during certain time windows. Consequently, the planning of maintenance has never priority on the production, to carry out preventive interventions. In this thesis, we propose some solutions to the problem of common and integrated maintenance and production planning tasks, with the objective to respect the intrinsic constraints of the problem. The objective of our work is double. On the one hand, we want to show the need for developing joint scheduling production/maintenance heuristic, to optimise production system reliability. In this context, we propose the adaptation of some heuristics approaches: constructive, iterative and evolutionary in the case of joint scheduling production/maintenance in a permutation flowshop. On the other hand, we studied the maintenance contribution to the robustness of these joint scheduling. The suggested model has a main goal: to register the generation of joint scheduling as a proactive approach. The integration of maintenance tasks during the generation of production scheduling of production, is to be put at the profit of their robustness.La maintenance et la production sont deux fonctions qui agissent sur les mêmes ressources. Cependant l'ordonnancement de leurs activités respectives est indépendant, et ne tient pas compte de cette contrainte. Les ressources (machines) sont toujours considérées comme disponibles à tout moment ou éventuellement durant certaines fenêtres de temps. Dès lors la planification de la maintenance n'est jamais prioritaire sur la production, pour effectuer des interventions préventives. Les travaux de cette thèse proposent quelques éléments de réponse au problème de la planification commune et intégrée des tâches de maintenance et de production, avec comme objectif le respect des contraintes intrinsèques au problème. L'objectif de notre travail est double. D'une part démontrer la nécessité de développer des heuristiques d'ordonnancement conjoint production/maintenance pour atteindre l'objectif d'optimisation de la sûreté de fonctionnement du système de production. Dans ce contexte nous avons proposé l'adaptation d'un certains nombre d'heuristiques des approches constructive, itérative et évolutive pour le cas de l'ordonnancement conjoint production/maintenance dans un atelier de type flowshop de permutation. D'autre part, nous avons étudié la contribution de la maintenance à la robustesse de ces ordonnancements conjoints. Le modèle proposé a pour objectif d'inscrire la génération d'ordonnancements conjoints comme une démarche proactive, et de démontrer que l'intégration de la maintenance lors de la génération des ordonnancements de production est à mettre au profit de la robustesse de ces derniers

An ant colony optimisation approach considering jointly scheduling and preventive maintenance in the flowshop sequencing problem

This paper presents INTACO, a hybrid Ant Colony Optimisation (ACO) algorithm coupled with a local search applied to the joint production and preventive maintenance scheduling problem in the flowshop sequencing problem. INTACO uses pheromone trail information to perform modifications on complete joint production and preventive maintenance solutions unlike more traditional ant systems that use pheromone trail information to construct complete solutions. Several new interesting features are proposed and evaluated. In particular, the use of a common representation of preventive maintenance and production data to optimise a common objective function which takes into account both preventive maintenance and production criteria with a new pheromone evaluation rule. Moreover, to enhance the performances of the proposed ACO algorithm, new local search procedures for ants are proposed. INTACO is tested on a set of non-standard test problems. We compare the results obtained to those of a genetic algorithm developed in previous works. The results and experiments carried out indicate that the proposed ant-colony algorithm provide very effective solutions for this problem.ant colony optimisation; ACO; production planning; joint scheduling; preventive maintenance; flow shop scheduling; sequencing; local search; pheromone trail information.

A Constraint Programming model for the scheduling problem with flexible maintenance under human resource constraints

International audienc

Résolution du problème de l'ordonnancement conjoint production / maintenance par colonies de fourmis.

International audienceL'article présente des algorithmes des colonies de fourmis pour la résolution du problème de l'ordonnancement conjoint production/maintenance dans un atelier de type flowshop de permutation selon deux stratégies séquentielle et intégrée. La stratégie séquentielle consiste à ordonnancer les tâches de production puis intégrer les tâches de maintenance, en prenant l'ordre d'exécution des tâches de production comme une contrainte forte. Alors que la stratégie intégrée consiste à ordonnancer simultanément les tâches de production et de maintenance . L'objectif est d'optimiser une fonction objectif qui prend en considération les critères de maintenance et de production en même temps. Une comparaison entre ces algorithmes et les algorithmes génétiques conclura ce travail

A new heuristic to solve the capacitated lot sizing problem in deteriorating production systems

International audienc