Recent Developments in Production Scheduling I
Date/Time: Monday 13:00-14:30
Room: Colonnade F
Chair: Chung-Yee Lee
Chair Address: TX A&M Univ., Dept. of IE, 238 Zachry Bldg., College Station, TX 77845 ,
Scheduling with Fixed Delivery Dates Nicholas G. Hall, Maseka Lesaona, Christopher N. Potts --- OH State Univ., Dept. of MS, 1775 College Rd., Columbus, OH 43210-1399, (email@example.com)
- We consider several scheduling problems where jobs are dispatched at¨ delivery dates which are fixed before the schedule is determined.¨ Single and parallel machine, flowshop, jobshop and openshop¨ environments are studied using various classical objectives. For¨ each problem, an algorithm or proof of intractability is provided.
Project Scheduling with Flexible Processors George Vairaktarakis --- Marquette Univ., College of Bus. Admin., Milwaukee, WI 53201-1881,
- We consider the problem of minimizing a cost function expressed as a¨ linear combination of the activity completion times of a project.¨ The project network is assumed to be a tree or forest. The project¨ activities are to be processed by processors with different flexible¨ characteristics.
Scheduling Stochastic Jobs with Asymmetric Earliness & Tardiness Penalties X. Q. Cai, S. Zhou --- Chinese Univ. of Hong Kong, Dept. of Systems Eng., Shatin NT, , Hong Kong
- We consider a stochastic counterpart of an earliness-tardiness¨ scheduling problem in which n stochastic jobs are to be processed on¨ a single machine. The objective is to minimize the expectation of a¨ weighted combination of the earliness penalty, the tardiness penalty¨ and the flow time penalty.
Heuristic Algorithms for Multiple Machine Scheduling with the Objective of Minimizing Total Weighted & Unweighted Tardiness Bahram Alidaee, Jaideep T. Naidu, Ed L. Gillenwater --- Univ. of MS, Mgmt. & Mktg. Dept., University, MS 38677 , (firstname.lastname@example.org)
- This study is concerned with minimization of total weighted and¨ unweighted tardiness in single and multiple machine scheduling. New¨ simple heuristic rules are presented, and some perturbation¨ heuristics based on so called 'noising method' and 'space smoothing¨ methods' are presented. Extensive computational experiment for¨ comparison of solutions generated by the heuristics are presented.
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