This paper focuses on three very similar evolutionary algorithms: genetic algorithm (GA), particle swarm optimization (PSO), and differential evolution (DE). While GA is more suitable for discrete optimization, PSO and DE are more natural for continuous optimization. The paper first gives a brief introduction to the three EA techniques to highlight the common computational procedures. The gener...

Job-shop scheduling problem is one of the most important fields in manufacturing optimization where a set of n jobs must be processed on a set of m specified machines. Each job consists of a specific set of operations, which have to be processed according to a given order. The Flexible Job Shop problem (FJSP) is a generalization of the above-mentioned problem, where each operation can be proces...

Flexible job-shop scheduling problem (FJSP) has been well known as one of the most difficult NP-hard combinatorial optimization problems. This problem FJSP is an extension of job-shop scheduling problem (JSP) which is to create a sequence of operations satisfying the precedence relationship together with assignment of time and resources for each operation. Thus, the FJSP model is closer to the ...

This paper deals with scheduling of tasks in cyclic flexible job shop scheduling problem (CFJSSP). We have proposed a new method of computing cyclic time for CFJSSP. This method is based on the known properties of the job shop problem as well as new properties of cyclic scheduling. We have developed two versions of proposed method: sequential and parallel. The parallel version is dedicated to t...

Volvo Aero has invested in a complex production cell containing a set of multipurpose machines. The problem of finding optimal schedules for this multitask cell is a complex combinatorial optimization problem which is recognized as a flexible job shop problem. This thesis proposes an approach to find such schedules using mathematical optimization. The mathematical models developed so far are pr...

The problem of efficiently scheduling production jobs on several machines is an important consideration when attempting to make effective use of a multimachines system such as a flexible job shop scheduling production system (FJSP). In most of its practical formulations, the FJSP is known to be NP-hard [8][9], so exact solution methods are unfeasible for most problem instances and heuristic app...

In this paper, we introduce a hybrid metaheuristic, the Variable Neighborhood Particle Swarm Optimization (VNPSO) algorithm, consisting of a combination of the Variable Neighborhood Search (VNS) and Particle Swarm Optimization(PSO). The proposed VNPSO algorithm is used for solving the multi-objective Flexible Job-shop Scheduling Problems (FJSP). Flexible job-shop scheduling is very important in...

0957-4174/$ see front matter 2010 Elsevier Ltd. A doi:10.1016/j.eswa.2010.08.145 ⇑ Corresponding author. E-mail address: [email protected] (L. Gao In this paper, we proposed an effective genetic algorithm for solving the flexible job-shop scheduling problem (FJSP) to minimize makespan time. In the proposed algorithm, Global Selection (GS) and Local Selection (LS) are designed to generat...

Hybrid algorithm based on Particle Swarm Optimization (PSO) and Simulated annealing (SA) is proposed, to solve Flexible Job Shop Scheduling with five objectives to be minimized simultaneously: makespan, maximal machine workload, total workload, machine idle time & total tardiness. Rescheduling strategy used to shuffle workload once the machine breakdown takes place in proposed algorithm. The hy...

During last decades, developing multi-objective evolutionary algorithms for optimization problems has found considerable attention. Flexible job shop scheduling problem, as an important scheduling optimization problem, has found this attention too. However, most of the multi-objective algorithms that are developed for this problem use nonprofessional approaches. In another words, most of them c...