Energitically efficient active vibration control of flexible structures

In this paper a control strategy called " Gloabal semi-active control" is presented and validated for a cantilever beam system. This strategy aims to achieve potential performance of fully active systems with a reduced energy supply of an amount comparable to this of semi-active strategies. The control approach is briefly presented, the law is offered and results for discrete systems (quarter vehicle example) are given. Independent modal space control (IMSC) study is performed and comparative results of the cantilever beam response to the different types of control are presented

An elitist quantum-inspired evolutionary algorithm for the flexible job-shop scheduling problem

The flexible job shop scheduling problem (FJSP) is vital to manufacturers especially in today’s constantly changing environment. It is a strongly NP-hard problem and therefore metaheuristics or heuristics are usually pursued to solve it. Most of the existing metaheuristics and heuristics, however, have low efficiency in convergence speed. To overcome this drawback, this paper develops an elitist quantum-inspired evolutionary algorithm. The algorithm aims to minimise the maximum completion time (makespan). It performs a global search with the quantum-inspired evolutionary algorithm and a local search with a method that is inspired by the motion mechanism of the electrons around an atomic nucleus. Three novel algorithms are proposed and their effect on the whole search is discussed. The elitist strategy is adopted to prevent the optimal solution from being destroyed during the evolutionary process. The results show that the proposed algorithm outperforms the best-known algorithms for FJSPs on most of the FJSP benchmarks

Solving multi-objective production scheduling problems with Tabu Search

Most of multiple criteria scheduling problems are NP-hard, so that exact procedures can only solve small problems and with two criteria. The complexity and the diversity of multiple criteria scheduling problems resulted in many alternative approaches to solve them. Exact and approximate procedures proposed in the literature are mainly dedicated to the problem to be solved and their performance depends on the problem data, on the criteria optimized, and are generally difficult to implement. We propose in this paper a Tabu Search approach to multiple criteria scheduling problems. The proposed procedure is a general flexible method, able to solve hard multiple criteria scheduling problems, easy to implement, and providing a set of potential efficient schedules. The criteria are any combination chosen from (C[sub max],T[sub max], L, N[sub T] and F)

Differential evolution for solving multi‐mode resource‐constrained project scheduling problems

International audienceno abstrac

Microscopic detection of bacillus Calmette–Guérin mycobacteria in bladder biopsy using fluorescence in situ hybridization

International audienc