Dynamic flexible job shop scheduling problems has been one of the important and strongly NP-hard problem of manufacturing systems for many years. Most of the proposed algorithms are based on priority rules; By using these rules, the arrived jobs go to a long queue of waited jobs and sometimes it takes a long time for a job to be processed. In this paper a new approach, integrating of priority r...

The problem of scheduling on the job shop floor is widely encountered in the manufacturing industry. However, generating good job shop schedules in a reasonable time remains a challenging problem, because of its inherent computational complexity. Dynamic job shop scheduling (DJSS) has been proven to be an intractable analytical problem and is largely solved by combinatorial analysis in traditio...

The general job-shop scheduling problem is known to be extremely hard. We describe a GA approach which produces reasonably good results very quickly on standard benchmark job-shop scheduling problems, better than previous eeorts using genetic algorithms for this task, and comparable to existing conventional search-based methods. The representation used is a variant of one known to work moderate...

The general job-shop scheduling problem is known to be extremely hard. We describe a GA approach which produces reasonably good results very quickly on standard benchmark job-shop scheduling problems, better than previous eeorts using genetic algorithms for this task, and comparable to existing conventional search-based methods. The representation used is a variant of one known to work moderate...

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...

A general model for job shop scheduling is described which applies to static, dynamic and non-deterministic production environments. Next, a Genetic Algorithm is presented which solves the job shop scheduling problem. This algorithm is tested in a dynamic environment under different workload situations. Thereby, a highly efficient decoding procedure is proposed which strongly improves the quali...

Flexible job shops are characterized by the existence of alternative –not necessarily identicalmachines, which permits parts to have different alternative routes in the shop. In a dynamic scheduling situation in which jobs continuously arrive over time, part routing rules are needed to deal with such routing flexibility as much as sequencing rules which define the order by which parts are admit...

The purpose of this study is to develop an effective scheduling methodology for a realistic flow shop sequencing problem. The flow shop consists of two machines where only the first machine has separable, external, and sequence dependent setup times. The length of setup times required for a job depends not on the immediately preceding job but on the job which is two steps prior to it. The probl...

Job shop scheduling (JSS) problems are optimisation problems that have been studied extensively due to their computational complexity and application in manufacturing systems. This paper focuses on a dynamic JSS problem to minimise the total weighted tardiness. In dynamic JSS, jobs’ attributes are only revealed after they arrive at the shop floor. Dispatching rule heuristics are prominent appro...