The First Canadian Furniture Company

2170 Words9 Pages
IE6560 – Deterministic Optimization
Project report
Instructor: Dr.Evrim Dalkiran Submitted by: Group 10

The first Canadian furniture company was established in Berlin (Kitchner), Ontario in 1830 and the next in Toronto in 1834. The industry developed considerably in the latter half of 19thcentury, mainly in Ontario. There were a few factories in Quebec before 1900 but the industry primarily developed after WWII.
Furniture is considered in economic terms as an ‘elastic commodity’ and is very sensitive to economic changes. It is an export oriented industry with 53% of production being shipped outside Canada and 95% of exports going to the US. Canada is the 5th largest exporter of furniture in the world operating at various
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2012 (US8788314 B2 – Grant)
Systems and methods for optimization of facility locations are disclosed, for example, wireless telecommunications facility locations. Among a plurality of cluster points, corresponding to wireless customers, optimal locations are determined for a predetermined number of cluster centers, each cluster center having a predetermined cluster radius that defines a cluster area. Among a plurality of cluster points, optimal facility locations are determined for a variable number of cluster centers, each cluster center having a minimum acceptable economic value.

Computer-based techniques providing greedy approaches for facility location and other similar problems – Kamal Jain, Mohmmad Mahdian, Amin Saberi – 16th May 2003 (US20040230680 A1 – Application)
Methods and apparatuses are provided that employ an improved greedy algorithm for addressing NP-Hard problems and others like them. The improved greedy algorithm considers possible local savings while also remaining significantly fast.

Problem context:
Structube, a furniture retailer chain in Canada, has a number of demand regions which has to be completely satisfied. The management is considering ‘five locations’ to open distribution centers (DCs) in order to cater to the demand regions. The company wants to know the number and location of DCs in order to minimize overall costs (costs associated with opening a facility and transportation costs when shipping from DCs to demand regions.)

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