The single-stage simultaneous lot sizing and scheduling problem was the object of study in this work. The problem aims to minimize the total inventory and backlog costs associated with producing N products on M parallel machines over T time-period. This thesis presented an extensive literature review on the differences found when modelling and implementing lot sizing and scheduling systems. We observed several studies used metaheuristics successfully to address large instances of these problems achieving near, and sometimes, optimal results. However, little has been found to demonstrate the capabilities of Evolutionary Algorithms in this field. A description of the methodology used to s problem : is given in terms of a Hybrid Evolutionary Algorithm which represents the problem using two novel ideas, i.e., sets of products are modelled as alleles of the solution encoded, and the use of a decoder process performing a Linear Programming, guides the solution towards overall optimality.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:501090 |
| Date | January 2009 |
| Creators | Staggemeier, Andrea Toniolo |
| Publisher | University of the West of England, Bristol |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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