Background

In operations research, a key problem involves balancing limited and uncertain resources for the maximization of a specific business objective under constraints (such as budget or time). Approaches for this problem are frequently domain-specific due to the variability in design variables.

For simpler problems such as hub-and-spoke placement design, one can use proximity (i.e. distance) as a target, leading to clustering-based approaches ((Ruan et al. 2016)) which focuses on minimizing resource distance to solve a specific task. In others probes, however, clustering based approaches do not show a clear advantage due to the fact that they involve resource allocation decisions on a non-linear space (unlike physical space) subject also to non-linear constraints (unlike time).

protease helps viruses replication

protected groups are features that one shouldn’t use: as in, these cannot be used:

• race
• color
• national origin
• religion
• age
• sex and gender
• sexual orientation
• physical or mental disability
• reprisal (grudges)

a protocol for a function \(f\) is a pair of functions \(A,B:\qty {0,1}^{*} \times \qty {0,1}* \to [0,1,STOP]\) whereby:

• on input \((x,y)\), we initialize round counter \(r=0\), and initial (empty) message \(b_0 = \epsilon\)
• while \(b_{r} \neq STOP\)
  • \(r++\)
  • if \(r\) is odd, then Alice sends \(b_{r} = A\qty(x, b_1 \cdots b_{r-1})\)
  • else Bob sends \(b_{r} = B\qty(y, b_{1} … b_{r-1})\)
• our function output \(b_{r-1}\), and we call \(r-1\) the number of rounds

protocol cost

the cost of a protocol \(P\) for \(f\) on \(n\) bit strings is: