scholarly journals Multiobjective Decision Making Policies and Coordination Mechanisms in Hierarchical Organizations: Results of an Agent-Based Simulation

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Stephan Leitner ◽  
Friederike Wall

This paper analyses how different coordination modes and different multiobjective decision making approaches interfere with each other in hierarchical organizations. The investigation is based on an agent-based simulation. We apply a modified NK-model in which we map multiobjective decision making as adaptive walk on multiple performance landscapes, whereby each landscape represents one objective. We find that the impact of the coordination mode on the performance and the speed of performance improvement is critically affected by the selected multiobjective decision making approach. In certain setups, the performances achieved with the more complex multiobjective decision making approaches turn out to be less sensitive to the coordination mode than the performances achieved with the less complex multiobjective decision making approaches. Furthermore, we present results on the impact of the nature of interactions among decisions on the achieved performance in multiobjective setups. Our results give guidance on how to control the performance contribution of objectives to overall performance and answer the question how effective certain multiobjective decision making approaches perform under certain circumstances (coordination mode and interdependencies among decisions).

Pharmaceutics ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 996
Author(s):  
Niels Lasse Martin ◽  
Ann Kathrin Schomberg ◽  
Jan Henrik Finke ◽  
Tim Gyung-min Abraham ◽  
Arno Kwade ◽  
...  

In pharmaceutical manufacturing, the utmost aim is reliably producing high quality products. Simulation approaches allow virtual experiments of processes in the planning phase and the implementation of digital twins in operation. The industrial processing of active pharmaceutical ingredients (APIs) into tablets requires the combination of discrete and continuous sub-processes with complex interdependencies regarding the material structures and characteristics. The API and excipients are mixed, granulated if required, and subsequently tableted. Thereby, the structure as well as the properties of the intermediate and final product are influenced by the raw materials, the parametrized processes and environmental conditions, which are subject to certain fluctuations. In this study, for the first time, an agent-based simulation model is presented, which enables the prediction, tracking, and tracing of resulting structures and properties of the intermediates of an industrial tableting process. Therefore, the methodology for the identification and development of product and process agents in an agent-based simulation is shown. Implemented physical models describe the impact of process parameters on material structures. The tablet production with a pilot scale rotary press is experimentally characterized to provide calibration and validation data. Finally, the simulation results, predicting the final structures, are compared to the experimental data.


Author(s):  
Ardeshir Raihanian Mashhadi ◽  
Behzad Esmaeilian ◽  
Sara Behdad

As electronic waste (e-waste) becomes one of the fastest growing environmental concerns, remanufacturing is considered as a promising solution. However, the profitability of take back systems is hampered by several factors including the lack of information on the quantity and timing of to-be-returned used products to a remanufacturing facility. Product design features, consumers’ awareness of recycling opportunities, socio-demographic information, peer pressure, and the tendency of customer to keep used items in storage are among contributing factors in increasing uncertainties in the waste stream. Predicting customer choice decisions on returning back used products, including both the time in which the customer will stop using the product and the end-of-use decisions (e.g. storage, resell, through away, and return to the waste stream) could help manufacturers have a better estimation of the return trend. The objective of this paper is to develop an Agent Based Simulation (ABS) model integrated with Discrete Choice Analysis (DCA) technique to predict consumer decisions on the End-of-Use (EOU) products. The proposed simulation tool aims at investigating the impact of design features, interaction among individual consumers and socio-demographic characteristics of end users on the number of returns. A numerical example of cellphone take-back system has been provided to show the application of the model.


2020 ◽  
Vol 88 ◽  
pp. 8-28
Author(s):  
Rimvydas Laužikas ◽  
Darius Plikynas ◽  
Vytautas Dulskis ◽  
Leonidas Sakalauskas ◽  
Arūnas Miliauskas

The impact of cultural processes on personal and social changes is one of the important research issues not only in contemporary social sciences but also for simulation of future development scenarios and evidence-based policy decision making. In the context of the theoretical concept of cultural values, based on the system theory and theory of social capital, the impact of cultural events could be analyzed and simulated by focussing on the construction/deconstruction of social capital, which takes place throughout the actor’s cultural participation. The main goal of this research is the development of measuring metrics, and agent-based simulation model aimed at investigation of the social impact of cultural processes.  This paper provides new insights of modeling the social capital changes in a society and its groups, depending on cultural participation. The proposed measurement metrics provide the measurement facility of three key components: actors, cultural events and events flow and social capital. It provides the initial proof of concept simulation results, - simplified agent-based simulation model showcase. The NetLogo MAS platform is used as a simulation environment.  


Kybernetes ◽  
2018 ◽  
Vol 47 (3) ◽  
pp. 605-635 ◽  
Author(s):  
Li Wang ◽  
Qingpu Zhang

Purpose Internet-based intangible network good (IING) has revolutionized multiple industries in recent years. This paper aims to reveal the laws of consumer’s decision-making on IING from a perspective of kinetic energy and potential energy. Design/methodology/approach In this paper, 4 aspects and 17 factors influencing IING adoption were generalized. Based on the theory of social physics, an agent-based simulation model, introducing physical energy theory to depict consumer’s decision-making, was built. An agent’s kinetic energy reflects the agent’s perceived effect of mass media on the agent’s decision-making on IING adoption. An agent’s potential energy reflects the agent’s perceived effect of social interactions on the agent’s decision-making on the adoption of IING. An agent’s final energy is the sum of the kinetic energy and potential energy, which reflects the agent’s final decision. Findings Some factors mainly influence the diffusion velocity, while other factors have a dramatic impact on both diffusion velocity and diffusion scale. The agent’s personality can make a difference at the early and middle stages of IING adoption, but a faint impact at the later stage because of the effects of network externalities and word of mouth. There is a critical value of the number of initial adopters which can dramatically speed up IING adoption. Practical implications This study provides new insights for firms on the effects of factors influencing consumers’ decision-making on IING adoption. Originality/value This paper defines a new kind of innovation, IING, and generalizes IING’s special characteristics. As a new application of social physics, the physical energy theory has been creatively introduced to depict consumer’s decision-making on IING adoption. A kinetic and potential energy model of IING adoption has been built. Based on simulation experiments, new insights of IING adoption have been gained.


Complexity ◽  
2010 ◽  
Vol 16 (3) ◽  
pp. 49-57 ◽  
Author(s):  
Hiroki Sayama ◽  
Dene L. Farrell ◽  
Shelley D. Dionne

2015 ◽  
Vol 72 (4) ◽  
Author(s):  
Erma Suryani ◽  
Rully Agus Hendrawan ◽  
Umi Salama ◽  
Lily Puspa Dewi

Several studies have been conducted regarding save energy in consuming the electricity through the simple changes in routines and habits. In the case of electricity consumption, consumer behavior might influenced by several factors such as consumer profession, season, and environmental awareness. In this paper, we developed an Agent Based Model (ABM) to analyze the behavior of different agents in consuming the electricity energy for each type of profession (agent) as well as their interaction with the environment. This paper demonstrates a prototype agent based simulation model to estimate the electricity consumption based on the existing condition and some scenarios to reduce the electricity consumption from consumer point of view. From the scenario results, we analyzed the impact of the save energy to increase the electrification ratio. 


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