Decomposition Methods for Complex Factory Scheduling by Irfan M. Ovacik

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 approach functionality, is encountered in lots of diverse production environments. Given the aggressive pressures confronted via many businesses in contemporary quickly altering worldwide markets, enhanced manufacturing unit scheduling should still give a contribution to a flrm's luck. besides the fact that, although an in depth physique of analysis on scheduling versions has been in life for a minimum of the final 3 a long time, lots of the thoughts presently in use in are particularly simplistic, and feature no longer made use of this physique of data. during this ebook we describe a scientific, long term study attempt geared toward constructing powerful 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 procedure with the tools and result of scheduling study to strengthen powerful approximate resolution techniques for those difficulties. the category of equipment we recommend, decomposition tools, represent a huge kin of heuristic methods to giant, NP-hard scheduling difficulties that are utilized in different environments as well as these studied during this book.

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2: Computational Burden of Various Solution Procedures The effectiveness of a decompoSition method, in terms of computational performance and the quality of the solutions obtained, depends heavily on the nature of the problem under study. If the subproblems identified in the decomposition 26 Chapter 2 -Industrial Context and Motivation interact heavily and in nonsimple ways, a decomposition method will be more difficult to develop. A greater degree of approximation may be necessary to obtain tractable subproblem structures, but may result in less accurate solutions; inaccurate models of the interactions between subproblems may result in infeasible solutions, requiring in turn the inclusion of procedures to restore feasibility.

Since operations are added one by one, infeasibilities can arise when the current operation requires a machine at a time when it is already occupied by another operation that was scheduled earlier. Hence the problem of maintaining feasibility, or constraint Decomposition Methods for Complex Factory Scheduling Problems 37 propagation. needs to be addressed explicitly. In this approach this is accomplished by a network representation of partial schedules similar to the disjunctive graph described in Chapter 4.

1. Wiley (1991). , "Decomposition Heuristics for Robust lob Shop Scheduling", Research Report 93T-008, Department of Industrial Engineering, Lehigh University (1993). , "Single Machine Scheduling Problems with Dynamic Arrivals: Decomposition Results and a Forward Algorithm", Naval Research Logistics 43, 709-719 (1996). , "Rolling Horizon Procedures for the Single Machine Dynamic Scheduling Problem", School of Industrial Engineering, Purdue University, West Lafayette, IN 479071287 (1995). , "A Modified Shifting Bottleneck Procedure for lob Shop Scheduling", International Journal of Production Research 31, 923-932 (1993).

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