  In this paper, we study a problem of truthful mechanism design for a
strategic variant of the generalized assignment problem (GAP) in a both
payment-free and prior-free environment. In GAP, a set of items has to be
optimally assigned to a set of bins without exceeding the capacity of any
singular bin. In the strategic variant of the problem we study, bins are held
by strategic agents, and each agent may hide its compatibility with some items
in order to obtain items of higher values. The compatibility between an agent
and an item encodes the willingness of the agent to receive the item. Our goal
is to maximize total value (sum of agents' values, or social welfare) while
certifying no agent can benefit from hiding its compatibility with items. The
model has applications in auctions with budgeted bidders. For two variants of
the problem, namely \emph{multiple knapsack problem} in which each item has the
same size and value over bins, and \emph{density-invariant GAP} in which each
item has the same value density over the bins, we propose truthful
$4$-approximation algorithms. For the general problem, we propose an
$O(\ln{(U/L)})$-approximation mechanism where $U$ and $L$ are the upper and
lower bounds for value densities of the compatible item-bin pairs.
