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 436-445 Optimisation for Productive Systems 1

Credit Points

7.1

Coordinator

Dr A. Wirth

Prerequisites

200-level Mathematics

Semester

1

Contact

18 lectures and 18 hours of tutorial/practice classes

Subject Description

Upon completion students should be able to model and solve a wide range of deterministic decision making problems for productive systems such as product mix, facility location and layout, assembly line balancing, scheduling, transportation and storage and retrieval by applying the techniques of mathematical programming, network analysis and heuristic problem solving, using a range of optimisation software tools.

Topics covered include; linear programming applied to production problems, integer programming models for assembly line balancing and scheduling, goal programming and facility location, facility layouts using quadratic programming. Dynamic programming and multistage processing operations. Heuristic solutions to machine sequencing and storage and retrieval problems.

Assessment

One examination not exceeding three-hours, assignments to a maximum of 5000 words or equivalent



Search : Index : Faculty of Engineering : Mechanical and Manufacturing Engineering
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Status:                   Official 1998
Last Modified:            Tuesday October 21 17:11
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Authorised by:            Academic Registrar
Email Enquiries:          Course_Information@registrar.unimelb.edu.au