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Single Machine Scheduling: Comparison of MIP Formulations and Heuristics for Interfering Job Sets

Abstract This research by studies the computational performance of four different mixed integer programming (MIP) formulations for single machine scheduling problems with varying complexity. These formulations are based on (1) start and completion time variables, (2) time index variables, (3) linear ordering variables and (4) assignment and positional date variables. The objective functions that are studied in this paper are total weighted completion time, maximum lateness, number of tardy jobs and total weighted tardiness. Based on the computational results, discussion and recommendations are made on which MIP formulation might work best for these problems. The performances of these formulations very much depend on the objective function, number of... (more)
Created Date 2012
Contributor Khowala, Ketan (Author) / Fowler, John (Advisor) / Keha, Ahmet (Advisor) / Balasubramanian, Hari J (Committee member) / Wu, Teresa (Committee member) / Zhang, Muhong (Committee member) / Arizona State University (Publisher)
Subject Industrial engineering / Mathematics / Computer science / Industrial Engineering / Interfering Job Sets / Mixed Integer Programming / Operations Research / Single Machine Scheduling / Two Agent
Type Doctoral Dissertation
Extent 119 pages
Language English
Reuse Permissions All Rights Reserved
Note Ph.D. Industrial Engineering 2012
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis