Modern algorithms for supply chain - Lecture 4.2


00:19 Introduction
04:33 Two definitions for ‘algorithm’
08:09 Big-O
13:10 The story so far
15:11 Auxiliary sciences (recap)
17:26 Modern algorithms
19:36 Outperforming “optimality”
22:23 Data structures - 1/4 - List
25:50 Data structures - 2/4 - Tree
27:39 Data structures - 3/4 - Graph
29:55 Data structures - 4/4 - Hash table
31:30 Magic recipes - 1/2
37:06 Magic recipes - 2/2
39:17 Tensor comprehensions - 1/3 - The ‘Einstein’ notation
42:53 Tensor comprehensions - 2/3 - Facebook’s team’s breakthrough
46:52 Tensor comprehensions - 3/3 - Supply chain perspective
52:20 Meta techniques - 1/3 - Compression
56:11 Meta techniques - 2/3 - Memoization
58:44 Meta techniques - 3/3 - immutability
01:03:46 Conclusion
01:06:41 4.2 Modern algorithms for supply chain - Questions?

Description

The optimization of supply chains relies on solving numerous numerical problems. Algorithms are highly codified numerical recipes intended to solve precise computational problems. Superior algorithms mean that superior results can be achieved with fewer computing resources. By focusing on the specifics of supply chain, algorithmic performance can be vastly improved, sometimes by orders of magnitude. “Supply chain” algorithms also need to embrace the design of modern computers, which has significantly evolved over the last few decades.