Research Article

Appling the Roulette Wheel Selection Approach to Address the Issues of Premature Convergence and Stagnation in the Discrete Differential Evolution Algorithm

Table 12

Comparison between the DDE and EDDE algorithms and the illustration of the stagnation situation for DDE and how EDDE avoids it.

DDE algorithm solutionsCostGapNonmatching degreeSolution stagnation startWaiting for solution improvement

πBest4511718121093622727003.84
π14511718121093622330403.840113 iteration
π24511718121093622330403.84098 iteration
π34511718121093622330403.840101 iteration
π44511718121093622330403.840103 iteration
π54511718121093622330403.84099 iteration
π64511718121093622330403.84085 iteration

EDDE algorithm solutionsCostGapNonmatching degreeGroup

πBest4511371012986122307042.80
π14121132758961102321643.45719 times
π24511718121093642330403.84827 times
π34511371012986122307042.8001 times
π44511101712836922357045.03714 times
π54211612175931082431008.331033 times
π665172481231110931572231.95114Regenerated

πBest: the πBest (bold) is the best solution in the population of the DDE and EDDE algorithms. Cost: the best value of the objective function obtained by DDE and EDDE algorithms by using equation (1). Nonmatching is the number of different facility locations between two solutions and calculated by using Algorithm 1. Group: a set of individuals with the same nonmatching degree as the best individual in EDDE algorithm. Gap: the best value obtained by equation (12). Solution stagnation start: the number of iterations that the solution has not changed (not improved) in the DDE algorithm, where max iteration is 1000. Waiting for solution improvement: the number of trials the EDDE algorithm waits for before considering the solution is stagnated and should be regenerated randomly (italic) the default value is 10 trials.