Interactive microcomputer graphic methods for smoothing craft layouts

Computer-aided layout planning has been under development since the early 1960s, and many layout programs are based on the powerful and well known program, CRAFT (Computerized Relative Allocation of Facilities Technique by Armour and Buffa 1963).

Unfortunately, the major drawback of these facilities layout programs is that they often create unrealistic and impractical designs since the resulting block layouts can have odd shapes. Most architectural building designs require that the rooms and departments be in the form of squares, rectangles or L-shapes. The traditional approach to rectifying this problem is to manually modify the block plans at the corresponding expense of time and effort.

This paper identifies the problems and proposes interactive graphic methods for smoothing CRAFT layouts. In addition, a new method for the assessment of layout efficiency is introduced to measure the quality of a layout before and after smoothing.     

Mean and standard deviation for the facilities design problem

An important problem in facilities design to find an assignment of n facilities to n locations so that total materials handling cost is minimized. For problems of moderate size, suboptimal solutions must be accepted since optimal algorithms are computationally infeasible. If the mean and standard deviation of the layout cost distribution is known, then statistical methods may be used to measure and compare the efficiencies of various suboptimal solutions as well as to monitor the efficiency of the same assignment under changing production environments. In this paper a new, simple algorithm to calculate the exact value of the standard deviation of the layout cost distribution is presented (the mean is easy). This algorithm has a computational efficiency of O(n²) arithmetic operations for a problem of size n × n, an improvement over previous methods which are either inexact or have a computational efficiency of O(n⁴). Results of tests verifying the accuracy and claimed efficiency of this algorithm, as implemented on a microcomputer, are also presented (about 0.85 second for a 30 × 30 problem).