Heuristics for Job-Shop Scheduling

Item

Title: en_US Heuristics for Job-Shop Scheduling
Creator: en_US Pasch, Kenneth Alan
Date: 2004-10-20T20:02:14Z
Date Available: 2004-10-20T20:02:14Z
Date Issued: en_US 1988-01-01
Identifier: en_US AITR-1036
uri: http://hdl.handle.net/1721.1/6847
Abstract: en_US Two methods of obtaining approximate solutions to the classic General Job-shop Scheduling Program are investigated. The first method is iterative. A sampling of the solution space is used to decide which of a collection of space pruning constraints are consistent with "good" schedules. The selected space pruning constraints are then used to reduce the search space and the sampling is repeated. This approach can be used either to verify whether some set of space pruning constraints can prune with discrimination or to generate solutions directly. Schedules can be represented as trajectories through a Cartesian space. Under the objective criteria of Minimum maximum Lateness family of "good" schedules (trajectories) are geometric neighbors (reside with some "tube") in this space. This second method of generating solutions takes advantage of this adjacency by pruning the space from the outside in thus converging gradually upon this "tube." One the average this methods significantly outperforms an array of the Priority Dispatch rules when the object criteria is that of Minimum Maximum Lateness. It also compares favorably with a recent relaxation procedure.
Extent: en_US 163 p.; 13869314 bytes; 5230492 bytes
Format: application/postscript; application/pdf
Language: en_US
Relation: en_US AITR-1036
Subject: en_US scheduling; en_US job-shop; en_US heuristic; en_US geometric

Item sets: AI Technical Reports (1964 - 2004)