Intraorganizational power verified interactive genetic algorithms for the design of logistics network

Prevalent in the organization where the decision-making conflicts, with decision aided software, the better design of logistics network can be achieved by the reconciliation between participants, which wrestle with others. If the decision model and aided software can partially refine the organizational power structure, thus the productive cooperation of the industry can be developed. Recently, the advancement of information and communication technologies (ICTs) has been shaping the globe production and thus modern logistics. In the wake of globalization such as global sourcing and marketing, the logistics network has become more complex. By now, the result is a high dimensional and complicated mathematical model but including no important qualitative factors such as worthy subjective preferences of experienced decision makers. Therefore, the interactive genetic algorithm (IGA) is firstly introduced to elicit the decision preferences and to compensate the possible deficiencies of the model for the logistics network design (LND). Except for our IGA had been verified by the power structure to be organization adaptive, we also proposed the multi-population probabilistic interactive genetic algorithms to ease the human fatigue problem often known in the applications of IGAs. By the experiment, the quantitative cost and qualitative power indeed gained proper balance by the proposed algorithms.