Polynomial approximation schemes are described in this paper for several strongly
NP-complete problems that have important applications in the areas of robot
motion planning, VLSI design, image processing, and location. These problems
appear in the contexts of covering and packing with convex objects. One of them
is the square packing problem, which comes up in the attempt to increase yield in
VLSI chip manufacture. For example, 64K RAM chips, some of which may be
defective, are available on a rectilinear grid placed on a silicon wafer. 2 x 2 arrays
of such nondefective chips could be wired together to produce 256K RAM chips.
In order to maximize yield, we want to pack a maximal number of such 2 X 2
arrays into the array of working chips on a wafer. (See the result of Berman et al.
[2], reviewed by Johnson [6], and the NP-completeness result of Fowler et al. [3].)