This diploma work deals with a dynamic multi-level multi-item lot sizing problem in a general production-assembly structure represented by a directed acyclic network, where each node may have several predecessors and successors. We assume stochastic demand, finite planning horizon consisting of discrete time periods, dynamic lot sizes, multiple constrained resources and time-varying cost parameters. The objective is to minimize the total costs over the planning horizon. This thesis includes overview of models with stochastic demand and also general description of genetic algorithm. Using different modifications of genetic algorithm I have proposed and implemented methods for solving a chosen model. Then I have made an experimental comparison of these method on selected problems.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:228087 |
| Date | January 2008 |
| Creators | Grulich, Martin |
| Contributors | Popela, Pavel, Dvořák, Jiří |
| Publisher | Vysoké učení technické v Brně. Fakulta strojního inženýrství |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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