In this paper we consider n-jobs, m-machines permutation flow shop scheduling problems. Flow shop scheduling is one of the most important combinational optimization problems. The permutation flow shop scheduling problems are NP-Hard (Non deterministic Polynomial time Hard). Hence many heuristics and metaheuristics were addressed in the literature to solve these problems. In this paper a hybrid ...

In this paper, we expose a new meta-heuristic based on the artificial behavior of bee colony (ABC) for solving the blocking permutation flow shop scheduling problem (BFSP) subject to regular objectives. On three main steps, the proposed algorithm iteratively solved the BFSP under three fixed measure (makespan, total flowtime, or total tardiness criterion). Discrete job permutations and operator...

A hybrid flow shop (HFS) is a generalized flow shop with multiple machines in some stages. HFS is fairly common in flexible manufacturing and in process industry. Because manufacturing systems often operate in a stochastic and dynamic environment, dynamic hybrid flow shop scheduling is frequently encountered in practice. This paper proposes a neural network model and algorithm to solve the dyna...

This paper deals with the problem of scheduling jobs in a parallel flow shop environment without buffers between machines and sequence-dependent setup times order to minimize maximum completion time jobs. The blocking constraint normally leads an increase due blockage machines, which can even more so when are considerable. Hence, heuristic solve this must take into account these specificities t...

This paper represents the metaheuristics proposed for solving a class of Shop Scheduling problem. The Bacterial Foraging Optimization algorithm is featured with Ant Colony Optimization algorithm and proposed as a natural inspired computing approach to solve the Mixed Shop Scheduling problem. The Mixed Shop is the combination of Job Shop, Flow Shop and Open Shop scheduling problems. The sample i...

An interesting research area is to solve scheduling problems using network flow models and algorithms. Most of the existing papers in this research area deal with scheduling problems with parallel machines (identical and / or uniform machines). This paper considers the specialized case and develops network flow models and algorithms to solve open shop and flow and job shop problems.

In this paper, scheduling problems in Flexible Manufacturing Cells (FMC) are studied. The scheduling objective is to minimize the makespan. We used a genetic algorithm (GA) for solving the optimization scheduling problem. We have developed one FMC with industrial characteristics with the objective of studying scheduling problems in these types of manufacturing systems (single machine scheduling...

In this paper, two tools to improve the performance of the NEHbased heuristics for the flow shop problem with and without buffer constraints are proposed. The first tool is the use of the reversibility property of the problems considered and the second one is a new tie-breaking strategy to be use in the insertion phase of the NEH heuristic. In addition, we have analyzed the behavior of five ini...