PROP1+M1S allocation doesn't exist

Dependencies:

  1. Fair division
  2. EFX
  3. EF1
  4. PROP1
  5. Minimum fair share
  6. AnyPrice share
  7. Maximin share allocations
  8. Restricted agents, pairwise fairness, and groupwise fairness
  9. Additive goods and binary marginals

Consider a fair division instance $\Ical = ([n], [m], V, w)$, where $n=3$, $m=7$, and $w = (7/12, 5/24, 5/24)$. The agents have identical additive valuations, and all items are goods of value 1 each.

Let $A$ be an allocation where $|A_1| = 3$ and $|A_2| = |A_3| = 2$. Then all of the following hold:

  1. An allocation $X$ is EFX iff $X = A$.
  2. An allocation $X$ is M1S iff $X = A$.
  3. $\WMMS_1 = 3$ and $\WMMS_2 = \WMMS_3 = 15/14$.
  4. An allocation $X$ is groupwise-WMMS iff $X = A$.
  5. $\APS_1 = 4$ and $\APS_2 = \APS_3 = 1$.
  6. $X$ is PROP1 iff $X$ is APS.
  7. $X$ is groupwise APS iff $X$ is APS.

Consequences of the above observations:

  1. M1S and PROP1 are not simultaneously achievable for this instance.
  2. Groupwise WMMS and EFX don't imply PROP1.
  3. APS doesn't imply M1S.

Proof

Observations 5 and 6 follow from binary-additive.html.

When every item has value 1, an agent is EF1-satisfied by an allocation iff she is EFX-satisfied by the allocation. It is easy to see that allocation $A$ is EFX (and hence also M1S).

Suppose for some allocation $X$, we have $|X_2| ≤ 1$ and agent 2 is EF1-satisfied by $X$. If $|X_2| = 0$, then $|X_1| ≤ 1$ and $|X_3| ≤ 1$, which is a contradiction. If $|X_2| = 1$, then $|X_3| ≤ 2$, and so $|X_1| ≥ 4$. Then \[ \frac{|X_1|}{w_1} ≥ \frac{48}{7} > \frac{24}{5} = \frac{|X_2|}{w_2}. \] This is a contradiction. Hence, if agent 2 is EF1-satisfied by $X$, then $|X_2| ≥ 2$. So, if agent 2 is M1S-satisfied by $X$, then $|X_2| ≥ 2$. Similarly, if agent 3 is M1S-satisfied by $X$, then $|X_3| ≥ 2$.

Suppose for some allocation $X$, we have $|X_1| ≤ 2$ and agent 1 is EF1-satisfied by $X$. Then for some $j \in \{2, 3\}$, we have $|X_j| ≥ 3$. Hence, \[ \frac{|X_1|}{w_1} ≤ \frac{24}{7} < \frac{24}{5} ≤ \frac{|X_j|-1}{w_j}, \] which is a contradiction. Hence, if agent 1 is EF1-satisfied by $X$, then $|X_1| ≥ 3$. So, if agent 1 is M1S-satisfied by $X$, then $|X_1| ≥ 3$. Hence, if $X$ is M1S, then $X = A$.

For any allocation $X$, define \[ f(X) = \min_{j=1}^n \frac{|X_j|}{w_j}. \] Then $\WMMS_i = w_i\max_X f(X)$ for all $i \in [n]$. If $|X_1| ≤ 2$, then $f(X) ≤ |X_1|/w_1 ≤ 24/7$. If $|X_2| ≤ 1$ or $|X_3| ≤ 1$, $f(X) ≤ 24/5$. $f(A) = \min(3 \times 12/7, 2 \times 24/5) = 36/7$. Hence, $\max_X f(X) = 36/7$, so $\WMMS_1 = 3$ and $\WMMS_2 = 15/14$.

If an allocation $X$ is groupwise WMMS, then $X$ is WMMS, so $X = A$.

Consider a fair division instance $\Ical' = ([2], [5], V, w')$, where $w' = (14/19, 5/19)$, the agents have identical additive valuations, and all items are goods of value 1 each. To show that $A$ is groupwise WMMS for $\Ical$, it suffices to show that allocation $A'$ is WMMS for $\Ical'$, where $|A'_1| = 3$, and $|A'_2| = 2$.

Let $X$ be any allocation for instance $\Ical'$. If $|X_1| ≤ 2$, then $f(X) ≤ |X_1|/w'_1 ≤ 19/7$. If $|X_2| ≤ 1$, then $f(X) ≤ |X_2|/w'_2 ≤ 19/5$. $f(A') = \min(3 \times 19/14, 2 \times 19/5) = 57/14$. Hence, $\max_X f(X) = 57/14$, so $\WMMS_1(\Ical') = 3$ and $\WMMS_2(\Ical') = 15/14$. Hence, $A'$ is WMMS for $\Ical'$. Hence, $A$ is groupwise WMMS for $\Ical$.

Observation 7 can be inferred by repeatedly applying binary-additive.html to restricted instances.

Dependency for: None

Info:

Transitive dependencies:

  1. /sets-and-relations/countable-set
  2. /analysis/sup-inf
  3. σ-algebra
  4. Set function
  5. Fair division
  6. Proportional allocation
  7. Restricted agents, pairwise fairness, and groupwise fairness
  8. Envy-freeness
  9. PROP1
  10. Minimum fair share
  11. EF1
  12. Maximin share of a set function
  13. Maximin share allocations
  14. Additive set function
  15. Subadditive and superadditive set functions
  16. PROP-unsat implies someone is superPROP
  17. EF1 implies PROP1
  18. Submodular function
  19. PROPx
  20. EFX
  21. Optimization: Dual and Lagrangian
  22. Dual of a linear program
  23. Linear programming: strong duality (incomplete)
  24. AnyPrice share
  25. Bound on k extreme values
  26. Additive goods and binary marginals