Abstract
Making proper decisions in today’s complex world is a challenging task for decision makers. A promising approach that can support decision makers to have a better understanding of complex systems is agent-based modeling (ABM). ABM has been developing during the last few decades as a methodology with many different applications and has enabled a better description of the dynamics of complex systems. However, the prescriptive facet of these applications is rarely portrayed. Adding a prescriptive decision-making (DM) aspect to ABM can support the decision makers in making better or, in some cases, optimized decisions for the complex problems as well as explaining the investigated phenomena. In this paper, first, the literature of DM with ABM is inquired and classified based on the methods of integration. Performing a scientometric analysis on the relevant literature lets us conclude that the number of publications attempting to integrate DM and ABM has not grown during the last two decades, while analysis of the current methodologies for integrating DM and ABM indicates that they have serious drawbacks. In this regard, a novel nature-inspired model articulation called optimal agent framework (OAF) has been proposed to ameliorate the disadvantages and enhance the realization of proper decisions in ABM at a relatively low computational cost. The framework is examined with the Bass diffusion model. The results of the simulation for the customized model developed by OAF have verified the feasibility of the framework. Moreover, sensitivity analyses on different agent populations, network structures, and marketing strategies have depicted the great potential of OAF to find the optimal strategies in various stochastic and unconventional conditions which have not been addressed prior to the implementation of the framework.
Highlights
In today’s complex world, decision making (DM) is a crucial task
In the simple version, which is used for explaining optimal agent framework (OAF), there are 1000 potential users as neutral agents in a fully connected network. e contact rate of each neutral agent with the other agents is considered a random variant from a uniform distribution between 1 and 3. ere are two marketers who represent the gladiators
One of them puts most of the effort into advertising, and the other one concentrates on attracting customers through Word of Mouth (WOM). ese two marketers will compete in the model which is developed by OAF to find a better marketing community members community members
Summary
In today’s complex world, decision making (DM) is a crucial task. Human beings can make wrong decisions because of mental limitations. Our minds cannot consider all the details and interactions among components in a complex system. We cannot predict the consequences of our decisions on different parts of complex systems precisely [1]. Ere are different OR models for different purposes. Analysts need to know the best possible decision considering the existing constraints and the objectives simultaneously. For this purpose, usually, optimization models will be employed. Ese kinds of OR models, which suggest the decision maker a closed-form optimal solution for the problem, are called prescriptive models Optimization models will be employed. ese kinds of OR models, which suggest the decision maker a closed-form optimal solution for the problem, are called prescriptive models
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