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**1 - 5**of**5**### Genetic algorithm integrated with artificial chromosomes for multi-objective flowshop scheduling problems

"... a b s t r a c t Recently, a wealthy of research works has been dedicated to the design of effective and efficient genetic algorithms in dealing with multi-objective scheduling problems. In this paper, an artificial chromosome generating mechanism is designed to reserve patterns of genes in elite ch ..."

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a b s t r a c t Recently, a wealthy of research works has been dedicated to the design of effective and efficient genetic algorithms in dealing with multi-objective scheduling problems. In this paper, an artificial chromosome generating mechanism is designed to reserve patterns of genes in elite chromosomes and to find possible better solutions. The artificial chromosome generating mechanism is embedded in simple genetic algorithm (SGA) and the non-dominated sorting genetic algorithm (NSGA-II) to solve single-objective and multiobjective flowshop-scheduling problems, respectively. The single-objective problems are to minimize the makespan while the multi-objective scheduling problems are to minimize the makespan and the maximum tardiness. Extensive numerical studies are conducted and the results indicate that artificial chromosomes embedded with SGA and NSGAII are able to further speed up the convergence of the genetic algorithm and improve the solution quality. This promising result may be of interests to industrial practitioners and academic researchers in the field of evolutionary algorithm or machine scheduling.

### 9 A hybrid genetic algorithm for the re-entrant flow-shop scheduling problem

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### 15+ MILLION TOP 1% MOST CITED SCIENTIST 12.2% AUTHORS AND EDITORS FROM TOP 500 UNIVERSITIES Molten Steel Level Control of Strip Casting Process Monitoring by Using Self-Learning Fuzzy Controller

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### « Evaluation et optimisation des systèmes innovants de production de biens et de services » METAHEURISTIQUES MULTIOBJECTIF POUR UN PROBLEME D’ORDONNANCEMENT DE

"... RESUME: Cet article concerne l’étude d’un problème multiobjectif d’ordonnancement des opérations sur des machines identiques et en parallèle avec des temps de préparation entre l’exécution des différentes opérations et des dates de début au plus tôt des tâches. Deux critères différents sont considér ..."

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RESUME: Cet article concerne l’étude d’un problème multiobjectif d’ordonnancement des opérations sur des machines identiques et en parallèle avec des temps de préparation entre l’exécution des différentes opérations et des dates de début au plus tôt des tâches. Deux critères différents sont considérés: le makespan (durée maximale de traitement) et la somme des retards. Deux méthodes de résolution sont proposées pour résoudre ce problème: NSGA-II (Non-dominated Sorting Genetic Algorithm) et SPEA-II (Strength Pareto Evolutionary Algorithm). Les résultats des deux méthodes sont comparés avec une méthode exacte qui consiste à énumérer toutes les solutions possibles pour les problèmes de petite taille. Pour les problèmes de grande taille, des critères d’évaluation sont utilisés pour comparer les deux algorithmes proposés (160 instances sont exécutées pour la comparaison de deux algorithmes). MOTS-CLES: Optimisation multiobjectif, machines parallèles, ordonnancement, NSGA-II, SPEA-II 1

### AN ALGORITHM TO SOLVE THE ASSOCIATIVE PARALLEL MACHINE SCHEDULING PROBLEM

, 2009

"... Effective production scheduling is essential for improved performance. Scheduling strategies for various shop configurations and performance criteria have been widely studied. Scheduling in parallel machines (PM) is one among the many scheduling problems that has received considerable attention in t ..."

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Effective production scheduling is essential for improved performance. Scheduling strategies for various shop configurations and performance criteria have been widely studied. Scheduling in parallel machines (PM) is one among the many scheduling problems that has received considerable attention in the literature. An even more complex scheduling problem arises when there are several PM families and jobs are capable of being processed in more than one such family. This research addresses such a situation, which is defined as an Associative Parallel Machine scheduling (APMS) problem. This research presents the SAPT-II algorithm that solves a highly constrained APMS problem with the objective to minimize average flow time. A case example from a make-to-order industrial product manufacturer is used to illustrate the complexity of the problem and