Journal of Theoretical and Applied Information Technology 20 th February 2015. Vol.72 No.2 © 2005 - 2015 JATIT & LLS. All rights reserved . ISSN: 1992-8645 www.jatit.org E-ISSN: 1817-3195 239 CAT SWARM OPTIMIZATION TO SOLVE FLOW SHOP SCHEDULING PROBLEM 1 ABDELHAMID BOUZIDI, 2 MOHAMMED ESSAID RIFFI lab. LAROSERI, Depart. of Computer Science. Chouaib Doukkali University, EL JADIDA, MOROCCO E-Mail : 1 mr.abdelhamid.bouzidi@gmail.com , 2 said@riffi.fr Abstract : Flow shop problem is a NP-hard combinatorial optimization problem. Its application appears in logistic, industrial and other fields. It aims to find the minimal total time execution called makespan. This research paper propose a novel adaptation never used before to solve this problem, by using computational intelligence based on cats behavior, called Cat Swarm Optimization, which is based on two sub modes, the seeking mode when the cat is at rest, and the tracing mode when the cat is at hunt. These two modes are combined by the mixture ratio. The operations, operators will be defined and adapted to solve this problem. To prove the performance of this adaptation, some real instances of OR-Library are used. The obtained results are compared with the best-known solution found by others methods. Keyword : Flow shop, scheduling, makespan, computational intelligent, cat swarm optimization. 1. INTRODUCTION The Flow shop scheduling [1] is one of the known problems in operational research. Given the whole applications fields, and the complexity of the problem, it has been a very active and prolific research area. To resolve this problem we should find the minimal make span by executing n jobs in m machine. Many optimization algorithms based on computational intelligence had been proposed to solve the flow shop-scheduling problem, such as simulated annealing [2-3], tabu search [3-5], harmony search [6-7], genetic algorithm [8-9], Ant Colony optimization [10-11], bee colony optimization [12], particle swarm optimization [13-15], and others. The present research paper aims to apply cat swarm algorithm never used before to solve FSSP. The research paper is organized as follows: in section II, a presentation and formulation of flow shop scheduling problem. In section III, a description of cat swarm optimization algorithm. In section VI, Cat swarm optimization applied to FSSP, and the results obtained by using some instance of OR-Library [21]. Finally, the conclusion and discussion. 2. FLOW SHOP SCHEDULING PROBLEM 2.1 PRESENTATION The flow shop-scheduling problem (FSSP) is a combinatorial optimization problem in class NP-HARD [16], simulated first in 1954 by Johnson [17]. FSSP is a set of n unrelated jobs that should be processed in the same order as m machines. The problem is to find the schedule of jobs that have the best minimal total time of execution of all the process called make span, by respecting some constraints, which are: - All jobs are independent, and available for processing at time zero. - The machines are continuously available from time zero onwards - Each machine can process one operation at a time. - Each job can be manufactured at a specific moment on a single machine - If a machine is not available, all the following jobs are assigned to a waiting queue. - The processing of a given job in a machine cannot be interrupted once started. A comprehensive list of these constraints, are grouped on categories, can be found in [1]. Setup times are sequence independent and are included in the processing. 2.2 FORMULATION OF PROBLEM: The FSSP is composed of n job J = {J 1 , J 2 … J n }, and m machine M = {M 1 , M 2 … M m }, each job is composed of m distinct operations O = {O 1 , O 2 … O m }. The operation in each job should respect the sequence of machine. Every operation is represented by a pair    and    (k∈ [1, (n*m)]), where    represents the machine on which the process o k will be