In this paper, we first introduce a generalized version of open shop scheduling (OSS), called generalized cyclic open shop scheduling (GCOSS) and then develop a hybrid method of metaheuristic to solve this problem. Open shop scheduling is concerned with processing n jobs on m machines, where each job has exactly m operations and operation i of each job has to be processed on machine i . However...

Flexible flow shop (or a hybrid flow shop) scheduling problem is an extension of classical flow shop scheduling problem. In a simple flow shop configuration, a job having ‘g’ operations is performed on ‘g’ operation centres (stages) with each stage having only one machine. If any stage contains more than one machine for providing alternate processing facility, then the problem...

The distributed blocking flow shop scheduling problem (DBFSP) allows modeling the scheduling process in companies with more than one factory. It configures production systems as flow shop lines where the blocking constraint must be considered. To the best of our knowledge, this variant of the distributed permutation flow shop scheduling problem has not been studied. In this working paper, we sh...

Flexible flow shop scheduling problem (also called blended flow shop scheduling problem) is a sort of complex Job Shop Scheduling problem. For the Flexible Flow Shop scheduling problem, only in very special cases, there are polynomial optimal algorithms. In most of the other cases, the problems are NP-Hard. It is a simplification of the original problem to solve Flexible flow shop scheduling wi...

We present Bar Systems: a family of very simple algorithms for different classes of complex optimization problems in static and dynamic environments by means of reactive multi agent systems. Bar Systems are in the same line as other Swarm Intelligence algorithms; they are loosely inspired in the behavior a staff of bartenders can show while serving drinks to a crowd of customers in a bar or pub...

Flexible flow shop scheduling problem (FFS) with unrelated parallel machines contains sequencing in flow shop where, at any stage, there exists one or more processors. The objective consists of minimizing the maximum completion time. Because of NP-completeness of FFS problem, it is necessary to use heuristics method to address problems of moderate to large scale problem. Therefore, for assessme...

One of the earliest results in flow shop scheduling theory is an algorithm given by Johnson’s [1] for scheduling jobs on two or three machines to minimize the total elapsed time whenever the processing times of jobs are random. The present paper is an attempt to develop a heuristic algorithm for two stages specially structured flow shop scheduling in which the processing times of the jobs a...

This paper studies the generalized normal distribution algorithm (GNDO) performance for tackling permutation flow shop scheduling problem (PFSSP). Because PFSSP is a discrete and GNDO generates continuous values, largest ranked value rule used to convert those values into ones make applicable solving this problem. Additionally, effectively integrated with local search strategy improve quality o...

In a shop floor of the industry, the routings which are based upon the jobs that need to be processed on different machines are one among the major activities and therefore the resource requirements are not based upon the quantity as in a flow shop but rather the routings for the products being produced. However, both job shop and flow shop production cope with a scheduling problem to find a fe...

Uncertainty plays a significant role in modeling and optimization of real world systems. Among uncertain approaches, fuzziness describes impreciseness while for ambiguity another definition is required. Vagueness is a probabilistic model of uncertainty being helpful to include ambiguity into modeling different processes especially in industrial systems. In this paper, a vague set based on dista...