Christian Stummer

TL;DR: The strengths and limitations of agent-based modeling in the context of innovation diffusion are critically examined, new insightsAgent-based models have provided are discussed, and promising opportunities for future research are outlined.

TL;DR: In this article, the authors introduce Pareto Ant Colony Optimization as an especially effective meta-heuristic for solving the portfolio selection problem and compare its performance to other heuristic approaches by means of computational experiments with random instances.

TL;DR: This paper describes a three-phase approach to assist research and development managers in obtaining the most attractive project portfolio which requires no a priori assumptions about the decision-maker's preferences.

TL;DR: This paper reviews the literature on quantitative modelling for research and development project selection and resource allocation and classifies and characterizes the various modelling approaches.

TL;DR: In this paper, the beneficial effect of P-ACO’s core function (i.e., the learning feature) is substantiated by means of a numerical example based on real world data and an integer linear programming preprocessing procedure that identifies several efficient portfolio solutions within a few seconds and correspondingly initializes the pheromone trails before running P- ACO is supplemented.