In this paper, we address the problem of finding a permutation schedule of n jobs in an m machine flow-shop environment that minimizes the maximum completion time Cmax (Makespan) of all jobs. The jobs are available at time zero and have sequence-dependent setup times on each machine. All parameters, such as processing and setup times, are assumed to be known with certainty. This problem is clas...

Past applications of artificial intelligence techniques to shop floor control tasks arc reviewed. In the area of resource allocation in distributed manufacturing D’stems, the issue of resource reconfiguration is identified as a neglected problem. A game theoretic planning model suitable for use in a distributed shop floor control environment is introduced. Autonomous machine controllers consult...

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...

This paper addresses the application of AI techniques in a practical OR problem , i.e. scheduling. Scheduling is a scientific domain concerning the allocation of tasks to a limited set of resources over time. The goal of scheduling is to maximize (or minimize) different optimization criteria such as the makespan (i.e. the completion time of the last operation in the schedule), the occupation ra...

Small machine shops typically do not have the resources to develop custom simulations of their operations or data translators to import their data from other manufacturing software applications. This paper presents an overview of an information model currently under development at the National Institute of Standards and Technology (NIST) to address this problem. The model provides neutral data ...

Tendency to optimization in last decades has resulted in creating multi-product manufacturing systems. Production planning in such systems is difficult, because optimal production volume that is calculated must be consistent with limitation of production system. Hence, integration has been proposed to decide about these problems concurrently. Main problem in integration is how we can relate pro...

In this paper, we analyze the characteristics of the job shop scheduling problem. A new genetic algorithm for solving the agile job shop scheduling is presented to solve the job shop scheduling problem. Initial population is generated randomly. Two-row chromosome structure is adopted based on working procedure and machine distribution. The relevant crossover and mutation operation is also desig...

In the last decade job shop scheduling problems have been subject to intensive research due to their multiple applications. Job shop scheduling is known as a strongly NPcomplete problem. In the job shop scheduling problems, processing times and due dates are very dynamically due to both human and machine resource factors. Fuzzy sets are used to model the uncertain processing times and due dates...