Bin packing: removing density restriction from config LP

Dependencies:

  1. Bin packing and Knapsack
  2. Bin packing: configuration LP
  3. Bin packing: density-restricted config LP

Let $I$ be a bin packing instance with $n$ items such that there are $m$ types of items, and all items of the same type are identical. Let $b_i$ be the number of items of type $i$. Let $A$ be the configuration matrix of $I$.

Let $g: I \mapsto \mathbb{R}_{\ge 0}$ be a function. For items of the same type, $g$ returns the same output. For a set $X$ of items, define $g(X) = \sum_{i \in X} g(i)$. Let $\lambda$ be a positive constant. Let there be a bin packing algorithm $P$ whose output satisfies at least one of these conditions:

Given a feasible solution $(\xhat, \yhat)$ of objective value $v$ to the $(g, \lambda)$-density-restricted configuration LP, we can get in polynomial time a feasible solution to the configuration LP of objective value at most $v + c$.

Proof outline

Let $\Yhat = \{i \in [m]: \yhat_i > 0\}$. If $\Yhat$ is empty, then $\xhat$ is a solution to the configuration LP. Otherwise, run $P$ on $Y$.

Suppose a bin has items $S$ and $g(S) \ge \frac{1}{\lambda}$. Let $\beta = \min_{i \in S} (\yhat_i/A[i, S])$. Define $\xtild$ and $\ytild$ as \begin{align} \xtild_C &= \begin{cases} \xhat_C & C \neq S \\ \xhat_C + \beta & C = S \end{cases} & \ytild_i &= \yhat_i - A[i, S]\beta \end{align} Then $(\xtild, \ytild)$ is a feasible solution to the density-restricted configuration LP and has a lower or equal objective value. Let $\Ytild = \{i \in [m]: \ytild_i > 0\}$. Then $|\Ytild| \le |\Yhat| - 1$.

Let $S_i$ be the set of items in the $i^{\textrm{th}}$ bin of the output of $P$ on $\Yhat$. Repeat this transformation till $g(S_i) < \frac{1}{\lambda}$ for all $i$ or $\Ytild = \{\}$. This will eventually happen since $|\Ytild| \le |\Yhat| - 1$. This means that the number of bins used is at most $c$. Let $H$ be the set of configurations of these bins. With slight abuse/overload of notation, let $(\xhat, \yhat)$ be the corresponding solution to the density-restricted configuration LP. Define $\xtild$ as \[ \xtild_C = \begin{cases} 1 & C \in H \\ \xhat_C & C \not\in H \end{cases} \] $\xtild$ is a feasible solution to the configuration LP and has objective value at most $v + c$.

Dependency for:

  1. 2D BP: APTAS for config LP

Info:

Transitive dependencies:

  1. Bin packing and Knapsack
  2. Bin packing: configuration LP
  3. Bin packing: density-restricted config LP