1

Fig. 1. A map illustrating the layout of stands within the Lincoln Tract in western Oregon (USA).

2

Fig. 2. The age class distribution of the hypothetical dataset.

Table 1. Threshold accepting instances.
Initial
threshold 		Iterations per
threshold 		Threshold
change 		Unsuccessful
iterations
per threshold 		Reversion
interval
(iterations)a) 		1-opt moves
iterationsb) 		2-opt moves
iterationsc) 		3-opt moves
iterationsd)
10 000 000 10 100 2000 0 ALL    
10 000 000 10 100 2000 3 ALL    
10 000 000 10 100 2000 6 ALL    
10 000 000 10 100 2000 9 ALL    
10 000 000 10 100 2000 0 100 10  
10 000 000 10 100 2000 3 100 10  
10 000 000 10 100 2000 6 100 10  
10 000 000 10 100 2000 9 100 10  
10 000 000 10 100 2000 0 100 10 3
10 000 000 10 100 2000 3 100 10 3
10 000 000 10 100 2000 6 100 10 3
10 000 000 10 100 2000 9 100 10 3
a) Reversion intervals: 0 = none, 3 = 1/3, 6 = 1/6, and 9 = 1/9
b) If 2-opt or 3-opt iterations are employed, 1-opt iterations are employed at the end of each of these sets
c) 2-opt iterations are employed immediately after each set of 100 1-opt iterations
d) 3-opt iterations are employed immediately after each set of 10 2-opt iterations
Table 2. Tabu search instances.
Number of
iterations 		Reversion
interval
(iterations)a) 		1-opt moves
iterationsb) 		2-opt moves
iterationsc) 		3-opt moves
iterationsd)
1 000 000 0 ALL    
1 000 000 3 ALL    
1 000 000 6 ALL    
1 000 000 9 ALL    
1 000 000 0 100 10  
1 000 000 3 100 10  
1 000 000 6 100 10  
1 000 000 9 100 10  
1 000 000 0 100 10 3
1 000 000 3 100 10 3
1 000 000 6 100 10 3
1 000 000 9 100 10 3
a) Reversion intervals: 0 = none, 3 = 1/3, 6 = 1/6, and 9 = 1/9
b) If 2-opt or 3-opt iterations are employed, 1-opt iterations are employed at the end of each of these sets
c) 2-opt iterations are employed immediately after each set of 100 1-opt iterations
d) 3-opt iterations are employed immediately after each set of 10 2-opt iterations
Table 3. Results of the s-metaheuristic search processes when applied to the forest management problem.
Search
process 		Reversion
interval
(iterations) 		Minimum (best)
solution value
(m3)2 		Maximum (worst)
solution value
(m3)2 		Average
solution value
(m3)2 		Standard
deviation of
solution values
(m3)2 		Average time
required
(seconds)
RD 0 74 894 37 996 939 3 620 631 6 199 511 37.2
RD 3 768 47 142 10 285 8397 39.3
RD 6 858 34 429 7656 6704 35.7
RD 9 980 32 937 10 424 7690 40.7
TA1 0 7462 18 287 902 386 149 2 072 861 15.5
TA1 3 1119 326 233 23 120 37 113 13.2
TA1 6 1932 98 510 19 328 17 162 14.3
TA1 9 1270 360 189 22 140 37 102 17.4
TA12 0 13 130 136 130 62 917 26 155 17.1
TA12 3 200 21 577 4026 4271 14.7
TA12 6 323 29 963 6153 5457 18.5
TA12 9 991 28 465 6994 5591 18.4
TA123 0 9923 330 688 68 858 39 769 29.2
TA123 3 173 34 262 5000 5463 21.1
TA123 6 329 41 796 7590 6688 24.8
TA123 9 217 61 753 9032 8971 25.7
TS1 0 969 517 278 20 692 63 162 98.6
TS1 3 217 1 959 049 73 424 323 694 106.0
TS1 6 7.406 2 205 650 33 171 238 905 102.0
TS1 9 19.612 11 248 1158 2077 112.3
TS12 0 27.029 674 329 139 212.0
TS12 3 3.625 4082 206 496 218.1
TS12 6 0.078 746 42 111 222.3
TS12 9 0.150 440 24 56 225.5
TS123 0 23.057 690 323 145 2219.1
TS123 3 2.979 5273 223 596 2137.1
TS123 6 0.395 462 38 78 2249.5
TS123 9 0.262 251 24 50 2102.4
(m3)2 = Cubic meters of harvest volume squared, the objective function unit value
RD = Raindrop method
TA1 = Threshold accepting with 1-opt moves only
TA12 = Threshold accepting with 1-opt and 2-opt moves
TA123 = Threshold accepting with 1-opt, 2-opt and 3-opt moves
TS1 = Tabu search with 1-opt moves only
TS12 = Tabu search with 1-opt and 2-opt moves
TS123 = Tabu search with 1-opt, 2-opt and 3-opt moves
Reversion intervals: 0 = none, 3 = 1/3, 6 = 1/6, and 9 = 1/9