![]() In: Proceedings of the 41st Annual Hawaii International Conference on System Sciences, p. Spohrer, J., Vargo, S.L., Caswell, N., Maglio, P.P.: The service system is the basic abstraction of service science. This process is experimental and the keywords may be updated as the learning algorithm improves. ![]() These keywords were added by machine and not by the authors. Our empirical results present a successful model for finding optimized resourced allocation settings in comparison with two different ABM simulated models on a sample of a real-life service delivery problem. This article introduces a new technique, which combines Agent Based Modeling (ABM) and Distribution Constraint Optimization (DCOP) to overcome these difficulties. Thirdly, mathematical optimization techniques often require the acquisition of knowledge in a central unit, which is problematic e.g. ![]() Secondly, having assumed that a fairly realistic model of the problem is simulated, finding optimal solutions requires an exhaustive search that is almost impossible in problems with a large search space. Simulation and optimization techniques generally suffer from three main drawbacks firstly, the limited knowledge and skill of researchers in modeling social complexities. humans, equipment and materials) to services increases profit. Service delivery optimization has an important impact on organizational profitability, where changes in allocation of resources (e.g.
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