In this paper, we analyze the characteristics of the dynamic job shop scheduling problem when machine breakdown and new job arrivals occur. A hybrid approach involving neural networks(NNs) and geneticalgorithm(GA) is presented to solve the dynamic job shop scheduling problem as a static scheduling problem. The objective of this kind of job shop scheduling problem is minimizing the completion ti...

The flexibility present in a job shop is an important determinant of the future success of the shop, since it increases the ability to deal with the changes a job shop is faced with in a dynamic environment. The presence of idle-time in a job shop schedule contributes considerably to this flexibility. By introducing an anticipation factor that preserves idletime in the scheduling process more f...

Process scheduling is a classical problem in the field of production planning and control; in particular, effective job shop scheduling remains an essential component in today’s highly dynamic and agile production environment. This paper presents unified framework for solving generic job shop scheduling problems based on the formulation of a job shop into three main classes of problem, namely, ...

Rapid development of the Internet of Things not only provides large amounts of data to the job-shop scheduling, but also proposes a great challenge for dynamic job shop scheduling. A dynamic job shop scheduling approach is proposed based on the data-driven genetic algorithm. Application examples suggest that this approach is correct, feasible and available. This approach can provide the technic...

Dynamic job shop scheduling that considers random job arrivals and machine breakdowns is studied in this paper. Considering an event driven policy rescheduling, is triggered in response to dynamic events by variable neighborhood search (VNS). A trained artificial neural network (ANN) updates parameters of VNS at any rescheduling point. Also, a multi-objective performance measure is applied as o...

Job shop scheduling is one of the most explored areas in the last few decades. Although it is very commonly witnessed in real-life situations, very less investigation has been carried out in scheduling operations of multi-level jobs, which undergo serial, parallel, and assembly operations in an assembly job shop. In this work, some of the dispatch rules, which have best performances in scheduli...

Dynamic job shop scheduling (DJSS) problems are combinatorial optimisation problems that have been extensively studied in the literature due to their difficulty and their applicability to real-world manufacturing systems, e.g., car manufacturing systems. In a DJSS problem instance, jobs arrive on the shop floor to be processed on specific sequences of machines on the shop floor and unforeseen e...

A model combining Discrete Event System (DES) and Multi-Agent System (MAS) is proposed to simulate a real-time job shop so that it can work as a test bed to systematically study the performance of control rules and algorithms in dynamic job shop scheduling. A definition of a generic job shop is given considering dynamic events, shop floor layout and the Material Handling System (MHS). It is fir...

We use the Akers-Friedman geometric approach to solve the two jobs job-shop problem when there is an earliness cost on the first operation and a tardiness cost on the last operation of each job. We then generalize the problem by imposing earliness and tardiness costs on each operation and finally, we solve it using a dynamic programming algorithm. KeywordsEarliness-tardiness scheduling, Polyn...

Dynamic scheduling algorithms are gaining more and more special attention for their satisfying robustness when confronted with unexpected events as well as their considerably high performance in scheduling. An organization structure for intelligent job shop scheduling based on MAS (Multiple Agents System) is put forward to achieve effective and efficient production. A hybrid multilayer agent st...