miga: Program for Constructing Minimum G-Aberration Designs

  1. Introduction
  2. Using miga
  3. Output
  4. Examples
  5. References

Introduction

miga is a program for constructing minimum G-aberration designs. The minimum G-aberration criterion proposed by Tang & Deng (1999) is a generalized version of the popular minimum aberration criterion of Fries & Hunter (1980). Designs constructed by miga include both regular and non-regular 2-level fractional factorial designs.

Let Dmxn be a design with m columns (factors) c1,c2,...,cm each of size n with n/2 +1's and n/2 -1's. We now use each row i of D to construct a vector Ji of length mC2+mC3+mC4. Define the first mC2 element as ci1ci2, ci1ci3,... the next mC3 as ci1ci2ci3, ci1ci2ci3, ... and the last mC4 as ci1ci2ci3ci4, ci1ci2ci3ci5 ...where cij is the ith entry of column cj. Let J=∑ Ji.

Now, define B2(D), B3(D) and B4(D) as 1/n2 x the sum of squares of of the first mC2, the next mC3 and the last mC4 elements of J respectively (see Eq. 2 of Ingram & Tang, 2005). Therefore, B2(D) provides the extent of aliasing between main effects in D, B3(D) provides the extent of aliasing between main effects and 2-factor interactions in D, and B4(D) provides the extent of aliasing between pairs of 2-factor interactions in D (see Ingram & Tang, 2005)

A design D is said to have less G2 aberration than D' if

  1. B2(D)<B2(D') or
  2. B2(D)=B2(D') and B3(D)<B3(D') or
  3. B2(D)=B2(D') and B3(D)=B3(D') and B4(D)<B4(D').

miga starts with a random design D with m columns, each having n/2 +1's and n/2 -1's. It then continues improving D with repect to the minimum G2 aberration criterion by exchanging the positions of +1 and -1 in each column of D. Details of the miga algorithm will be reported elsewhere.

In this note Wu & Hamada (2000) is abbreviated as WH.

Using miga

Let's assume all Gendex class files are in the directory c:\gendex and suppose you want to construct a 27-2 resolution VI design. At the working directory, issue the following command at the command prompt (case is important and no space is allowed before/after the equal sign):
java -cp c:\gendex miga m=7 ms=3 n=32

miga will start running and after try 1, the plan of the constructed design for this try will be displayed at the terminal window and then miga stops:

miga 10.0: Program for Constructing Minimmum G-Aberration Designs
(c) 2018 Design Computing (http://designcomputing.net/)

Note: Best design for 7 2-level factors in 32 runs.

try	iter	B2	B3	B4
1	14	0	0	1

Design for try 1 using seed 1534226728132:

(1)	(2)	(3)	(4)	(5)	(6)	(7)	
1	1	1	1	1	1	1	
1	1	1	1	-1	-1	1	
1	1	1	-1	1	1	-1	
1	1	1	-1	-1	-1	-1	
1	1	-1	1	1	-1	-1	
1	1	-1	1	-1	1	-1	
1	1	-1	-1	1	-1	1	
1	1	-1	-1	-1	1	1	
1	-1	1	1	1	-1	-1	
1	-1	1	1	-1	1	-1	
1	-1	1	-1	1	-1	1	
1	-1	1	-1	-1	1	1	
1	-1	-1	1	1	1	1	
1	-1	-1	1	-1	-1	1	
1	-1	-1	-1	1	1	-1	
1	-1	-1	-1	-1	-1	-1	
-1	1	1	1	1	-1	-1	
-1	1	1	1	-1	1	-1	
-1	1	1	-1	1	-1	1	
-1	1	1	-1	-1	1	1	
-1	1	-1	1	1	1	1	
-1	1	-1	1	-1	-1	1	
-1	1	-1	-1	1	1	-1	
-1	1	-1	-1	-1	-1	-1	
-1	-1	1	1	1	1	1	
-1	-1	1	1	-1	-1	1	
-1	-1	1	-1	1	1	-1	
-1	-1	1	-1	-1	-1	-1	
-1	-1	-1	1	1	-1	-1	
-1	-1	-1	1	-1	1	-1	
-1	-1	-1	-1	1	-1	1	
-1	-1	-1	-1	-1	1	1	

Note: Non-zero elements in J:
4567 (32)

Note: Resolution IV (all main effects and 15 2fi's 12 13 14 15 16 17 23 24 25 26 27 34 35 36 37 are clear).
Note: The first 5 column(s) form the base design.
Note: miga used 0.205 seconds.
Note: miga.htm has been created.

Note that the default random seed is the one obtained from the system clock and the default number of tries is 1000. You can change these default values by specifying the seed number and the number of tries, e.g.

java -cp c:\gendex miga m=7 ms=3 n=32 seed=1234 tries=1000

We now modify the definition of clear and strongly clear of an effect in WH p. 156 to suite our explanation of the resolution options. A main effect or 2-factor interaction (2fi) is clear if it is orthogonal to other main effects and 2fi's. A main effect is strongly clear if it is clear and any 2fi's involving it is clear. A 7-factor design with the first three strongly clear factors 1-3, for example, should have the following 15 clear 2fi's: 12, 13, 14, 15, 16, 17, 23, 24, 25, 26, 27, 34, 35, 36 and 37 (Example 3).

A constructed design will be classified into the following resolution type:

  1. III: In a resolution III design, main effects are pair-wise orthogonal. Resolution III design can be constructed more efficiently with the NOA module of the Gendex DOE toolkit.
  2. V: In a resolution V design, all main effects are strongly clear.
  3. IV (with the first ms main effects strongly clear): In a resolution IV design, all main effects are clear. However, the numbers of ms (<m), the first strongly clear main effects of two resolution IV designs of the same size might differ. To construct the resolution IV designs for 6≤m≤11, and n=16, 32 and 64 (Examples 3-9), you have to use Table 1. In this table, the preset values of ms are given for each value of m and n. The numbers in the brackets in this table refer to the numbers of clear 2fi's associated with each value of ms. Note that for m=9 and n=32, you have two choices of ms (Examples 5-6).

    Table 1. Preset values of ms
    m n=16 n=32 n=64
    6 0 (0) - -
    7 0 (0) 3 (15) -
    8 0 (0) 2 (13) -
    9 - 1 (8)
    2 (15)
    5 (30)
    10 - 0 (0) 4 (30)
    11 - 0 (0) 3 (27)

miga can also augment additional columns to existing design. To construct a 28-2 resolution VI design, you can add an additional column to the 27-2 design constructed in the previous example which is now used as a base design with the following command:

java -cp c:\gendex miga in=miga.in m=8

Output

The result of the best try is displayed at the terminal window and is also saved in the file miga.htm in the working directory. This file can be read by a browser such as IE or Google Chrome. Information for this try includes:

  1. Try number;
  2. The number of iterations;
  3. B2(D), B3(D) B4(D) values. miga automatically stops when all three values become 0.
  4. The design plan and the associated random seed.
  5. The non-zero elements in J if any.
  6. Resolution of the design.
  7. A list of clear 2fi's if the design is of resolution IV.
  8. The time in seconds miga used to construct the above design.

Examples

  1. A 26-2 resolution IV design (http://designcomputing.net/gendex/miga/m1.html).
  2. A 27-2 resolution IV design (http://designcomputing.net/gendex/miga/m2.html).
  3. A 28-2 resolution IV design (http://designcomputing.net/gendex/miga/m3.html).
  4. A 27-2 resolution IV design with 3 strongly clear main effects (http://designcomputing.net/gendex/miga/m4.html).
  5. A 28-3 resolution IV design with 2 strongly clear main effects (http://designcomputing.net/gendex/miga/m5.html).
  6. A 29-4 resolution IV design with 1 strongly clear main effect (http://designcomputing.net/gendex/miga/m6.html).
  7. A 29-4 resolution IV design with 2 strongly clear main effects (http://designcomputing.net/gendex/miga/m7.html).
  8. A 29-3 resolution IV design with 5 strongly clear main effects (http://designcomputing.net/gendex/miga/m8.html).
  9. A 210-4 resolution IV design with 4 strongly clear main effects (http://designcomputing.net/gendex/miga/m9.html).
  10. A 211-3 resolution IV design with 3 strongly clear main effects (http://designcomputing.net/gendex/miga/m10.html).

Notes:

References

Fries, A. & Hunter, W. G. (1980) Minimum Aberration 2k-p designs. Technometrics 22, 601-608.
Ingram, D. & Tang, B. (2005) Minimum G Aberration design construction and design tables for 24 runs. J. of Quality Technology 37, 101-114.
Tang, B. & Deng, L.Y. (1999) Minimum G2-aberration for nonregular fractional factorial designs. The Annals of Statistics 27, 1914-1926.
Wu, C.F.J & M. Hamada (2000) Experiments: Planning, Analysis and Parameter Design Optimization. New York: John Wiley & Sons, Inc.

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