By Irfan M. Ovacik
The manufacturing unit scheduling challenge, that of allocating machines to competing jobs in production amenities to optimize or at the least enhance procedure functionality, is encountered in lots of assorted production environments. Given the aggressive pressures confronted by way of many businesses in modern day quickly altering worldwide markets, more desirable manufacturing facility scheduling should still give a contribution to a flrm's luck. although, even if an intensive physique of analysis on scheduling types has been in life for a minimum of the final 3 a long time, lots of the ideas at present in use in are quite simplistic, and feature now not made use of this physique of data. during this ebook we describe a scientific, long term examine attempt geared toward constructing potent scheduling algorithms for complicated production amenities. We concentrate on a speciflc business context, that of semiconductor production, and take a look at to mix wisdom of the actual construction method with the equipment and result of scheduling learn to boost powerful approximate answer tactics for those difficulties. the category of equipment we advise, decomposition equipment, represent a wide relatives of heuristic ways to giant, NP-hard scheduling difficulties that are utilized in different environments as well as these studied during this book.
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Extra info for Decomposition Methods for Complex Factory Scheduling Problems
Many of these issues for workcenter-based decompositions will be addressed in later chapters of this book. The issues regarding job-based and operation-based decompositions are similar in essence - how to maintain feasibility or, equivalently, how to use global information in solving the subproblems so that a feasible, highquality schedule results. Both the heuristic search approaches and the Lagrangian Relaxation approaches have so far demonstrated their feasibility and promise on relatively small sets of test problems.
A TAXONOMY OF DECOMPOSITION METHODS FOR FACTORY SCHEDULING PROBLEMS Over the last three decades, a variety of decomposition methods for FSPs have been developed. A logical basis for classifying these methods is the nature of the subproblems. There are two main axes along which an FSP can be decomposed: time and a given set of scheduling entities. We shall define a scheduling entity to be an object subject to a scheduling decision. The basic scheduling entities in the FSPs treated in this book are machines and operations.
The remaining flow time of the job is estimated using a technique called Lead Time Iteration, which is based on a deterministic simulation of the shop. Initial estimates of the flow times are derived using a simple multiple of the processing times of the remaining operations. A schedule is then constructed for the shop using a dispatching rule which makes use of the flow time estimates. A new estimate of the flow times is then derived as a weighted average of the previous estimates and the actual flow times realized in the simulated schedule.