Pierre Borne

Bio: Pierre Borne is an academic researcher from École centrale de Lille. The author has contributed to research in topics: Genetic algorithm & Job shop scheduling. The author has an hindex of 19, co-authored 52 publications receiving 2294 citations. Previous affiliations of Pierre Borne include Centre national de la recherche scientifique & École Centrale Paris.

Approach by localization and multiobjective evolutionary optimization for flexible job-shop scheduling problems

Abstract: Traditionally, assignment and scheduling decisions are made separately at different levels of the production management framework. The combining of such decisions presents additional complexity and new problems. We present two new approaches to solve jointly the assignment and job-shop scheduling problems (with total or partial flexibility). The first one is the approach by localization (AL). It makes it possible to solve the problem of resource allocation and build an ideal assignment model (assignments schemata). The second one is an evolutionary approach controlled by the assignment model (generated by the first approach). In such an approach, we apply advanced genetic manipulations in order to enhance the solution quality. We also explain some of the practical and theoretical considerations in the construction of a more robust encoding that will enable us to solve the flexible job-shop problem by applying the genetic algorithms (GAs). Two examples are presented to show the efficiency of the two suggested methodologies.

Tuning PID controller using multiobjective ant colony optimization

Abstract: This paper treats a tuning of PID controllers method using multiobjective ant colony optimization. The design objective was to apply the ant colony algorithm in the aim of tuning the optimum solution of the PID controllers (Kp, Ki, and Kd) byminimizing the multiobjective function. The potential of using multiobjective ant algorithms is to identify the Pareto optimal solution. The other methods are applied to make comparisons between a classic approach based on the "Ziegler-Nichols" method and a metaheuristic approach based on the genetic algorithms. Simulation results demonstrate that the new tuning method using multiobjective ant colony optimization has a better control system performance compared with the classic approach and the genetic algorithms.

Influence of a Jerk Controlled Movement Law on the Vibratory Behaviour of High-Dynamics Systems

Abstract: The focus of this paper is on the formalisation of the influence of a jerk-controlled movement law on the vibrations of industrial high-speed systems, i.e. systems for which axes are submitted to significant dynamical demands. Analysis of the physical relationship between the jerk limit and the maximum vibratory amplitude is conducted on a simplified axis drive model that simultaneously accounts for axis control parameters and predominant mode effects. Experimental measurements conducted on three tests-setups demonstrate the effectiveness of the proposed approach in accurately predicting the evolution of the vibration level according to the constant jerk stages time and the axis drive parameters.

Phd by thesis

Abstract: Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

Approach by localization and multiobjective evolutionary optimization for flexible job-shop scheduling problems

Abstract: Traditionally, assignment and scheduling decisions are made separately at different levels of the production management framework. The combining of such decisions presents additional complexity and new problems. We present two new approaches to solve jointly the assignment and job-shop scheduling problems (with total or partial flexibility). The first one is the approach by localization (AL). It makes it possible to solve the problem of resource allocation and build an ideal assignment model (assignments schemata). The second one is an evolutionary approach controlled by the assignment model (generated by the first approach). In such an approach, we apply advanced genetic manipulations in order to enhance the solution quality. We also explain some of the practical and theoretical considerations in the construction of a more robust encoding that will enable us to solve the flexible job-shop problem by applying the genetic algorithms (GAs). Two examples are presented to show the efficiency of the two suggested methodologies.