Gord Moore, founder of Moore AI Machines (MAIM) sat at his desk awestruck by what was happening. After two years of sacrifice, sleeping on a cot in the office and eating No Name KD, the “Ai Kaizen” would be introduced to the world in two months. The Ai Kaizen was an Artificial Intelligence machine offering free-standing, off-line, distributed AI capabilities, but when used online was still capable of shared generative artificial intelligence through a dedicated MAIM sub-net.

Four companies had signed on as distributors for the launch set to take place October 1, with orders for the launch of 200,000 machines.

Distributor Units Ordered Abacus Computers45,000Binary Systems 40,000Copernicus Computing65,000Dyson Distribution50,000

Manufacturing would be out-sourced to at least three, but possibly four, companies located on the Pacific rim, which created a two-month lead time. This lead time was split roughly evenly between actual manufacturing and container shipping via sea then rail or truck once they arrive at one of two west coast container terminals. The units would be shipped “white box” from the manufacturer to the distributor, with only the serial numbering sequence differentiating the manufacturer.

The boxes containing the Ai Kaizen machines are 0.575 x 0.21 x 0.475 meters, meaning that exactly 1000 unit fit in a 40-foot standard shipping container. “That’s quite convenient,” thought Gord, “I can simply plan in terms of containers of machines. I simply need to determine the best way to get 200 containers from the Far East to their distributors, subject to whatever constraints there might be.

And there are many constraints. For each manufacturer, that could be contracted, there are both maximum and minimum production numbers, as well as minimum and maximum shipping capacities. All values in this table is number of containers:

As well, the costs in dollars, are different by manufacturer and container port destination:

For at least the first month of production MAIM would need to send an engineer to be onsite to handle any issues that arise in real-time. The cost shown in the table above covers accommodation and meals.

There is no requirement hat all four companies are hired to do the manufacturing, although it is evident from the table on the previous page that at least three companies are required.

For planning purposes, the container ports have a requirement to provide a minimum and maximum number of containers that will be send through their terminal, but they accept fairly wide ranges. Long Branch is expecting between 40 and 130 containers, while Vancouver is expecting between 60 and 140.

Once in North America, the containers must be shipped to the distributors’ warehouses where labeling will be affixed to white boxes. The trucking and rail companies also have maximum and minimum requirements, in number of containers.

Gord had no idea when he sat down to model this that there would be so many constraints, He needs to devise his production and shipping plan quickly or risk delaying the launch. As the four distributors are all paying the same price for the Ai Kaizen machines, minimizing cost is that same as maximizing profit.

NOTE: The decision-making unit is containers of Ai Kaizen machines, which equates to 1000 units. Do not change the unit for modelling purposes – it simply adds unnecessary zeroes and I assure you, no container will be fractional in a properly constructed model, and you do not need to constrain you container decision variables to integer.

DELIVERABLE #1:

Determine the optimal production allocation and most cost-efficient routing of the finished units, and the cost of the plan, based on the narrative above. Tabular presentation of the results with appropriate commentary is expected

DELIVERABLE #1a:

Gord wants to know the unit cost of each inclusive of the on-site engineer and the trans-Pacific shipping, and how much spare capacity each manufacturer has should it be necessary to reallocate production. Report these by filling-in the following table to be included in your report.

DELIVERABLE #1b:

Gord wants to know how much spare shipping capacity there is at each port and along each route from port to distributor. Report these by filling-in the following table to be included in your report.

DELIVERABLE #2

Gord is concerned that the cost structure at Nippon AI is substantially higher. MAIM’s Director of Procurement and Nippon AI’s Manager of Supply Chain Partnerships conductred a series of meetings to see what could be done to make Nippon AI more competitive, with two results: (1) $40 dollars of Value Added Tax that should not apply to exported goods was included in the unit cost, thus lowering Nippon AI’s manufacturing cost per unit to $710, and (2) The state-run freight handler will waive demurrage fees of $800 per container, reducing the trans-Pacific shipping costs to $5000 and $5100 to Long Beach and Vancouver, respectively. What would be the optimal production allocation, most cost-efficient routing and the cost of the plan, with these changes?

DELIVERABLES #2a and #2b:

Repeat DELIVERABLES #1a and #2b incorporating the changes for Nippon AI resulting from discussions described for DELIVERABLE #2.

DELIVERABLE #3

Gord just received text messages from the CEOs of Copernicus and Dyson each saying they wanted another 10,000 units. Is this feasible as currently constrained. If not, what are the bottlenecks that would have to be changed and by how much?
 

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