Simulation model of supply networks development

2019 ◽  
Author(s):  
Petr Fiala ◽  
Martina Kuncová
Keyword(s):  
Simulation Model ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Initial Conditions ◽  
Fitness Function ◽  
Network Systems ◽  
Network Growth ◽  
Fitness Value ◽  
Complex Adaptive ◽  
Fixed Structure

The paper is dedicated to network development in the network economy. The current economy needs to look not only at networks with only dynamic flows and with a fixed structure, but as a dynamic system its structure evolves and changes. Structure and behaviour dynamics of network systems can be modelled as complex adaptive systems and use agent-oriented simulation to demonstrate origin, perturbation effects, and sensitivity with regard to initial conditions. Survival of firms is associated with the value of so-called fitness function. Firms whose fitness value falls below a certain threshold will be extinguished. In this way, it is possible to partially model network growth. A simulation model in SIMUL8 is proposed.

scholarly journals Smallholder value chains as complex adaptive systems: a conceptual framework

2018 ◽  
Vol 8 (1) ◽  
pp. 14-33 ◽  
Author(s):  
Alastair Orr ◽  
Jason Donovan ◽  
Dietmar Stoian
Keyword(s):  
Conceptual Framework ◽  
Complex Adaptive Systems ◽  
Value Chain ◽  
Adaptive Systems ◽  
Initial Conditions ◽  
Sudden Change ◽  
Value Chains ◽  
Limited Attention ◽  
Content Type ◽  
Complex Adaptive

Purpose Smallholder value chains are dynamic, changing over time in sudden, unpredictable ways as they adapt to shocks. Understanding these dynamics and adaptation is essential for these chains to remain competitive in turbulent markets. Many guides to value chain development, though they focus welcome attention on snapshots of current structure and performance, pay limited attention to the dynamic forces affecting these chains or to adaptation. The paper aims to discuss these issues. Design/methodology/approach This paper develops an expanded conceptual framework to understand value chain performance based on the theory of complex adaptive systems. The framework combines seven common properties of complex systems: time, uncertainty, sensitivity to initial conditions, endogenous shocks, sudden change, interacting agents and adaptation. Findings The authors outline how the framework can be used to ask new research questions and analyze case studies in order to improve our understanding of the development of smallholder value chains and their capacity for adaptation. Research limitations/implications The framework highlights the need for greater attention to value chain dynamics. Originality/value The framework offers a new perspective on the dynamics of smallholder value chains.

Adaptive Walks and Fitness Peak Climbing: Language Learning as Inducing Adaptive Change in L2 Systems

2020 ◽  
Vol 1 (1) ◽  
pp. 29-42
Author(s):  
William Kumai
Keyword(s):  
Language Learning ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Fitness Landscape ◽  
Landscape Changes ◽  
Competence Level ◽  
Fitness Value ◽  
Learning Conditions ◽  
Complex Adaptive ◽  
Adaptive Walks

This paper adopts the perspective of students, groups, and entire classes as being complex adaptive systems, or CAS. Two important concepts from complexity theory, adaptive walks and fitness landscapes, can be used to create optimal language learning conditions for producing changes in students’ L2 systems. Every configuration of L2 traits a student might have can be assigned a fitness value, that is, an L2 competence level. The set of all such values creates an abstract landscape, the fitness landscape. By changing traits, the position on the landscape changes, meaning a student can take a journey on the landscape, known as an adaptive walk, in the search for higher peaks, that is, higher competence. The goal becomes establishing conditions in which adaptive walks are encouraged. Several L2 activities are introduced as applications of these ideas. 学生、グループ、およびクラス全体は、複雑系適応システムと考えられる。複雑系理論における2つの概念、アダプティブ・ウォーク(適応型歩行)とフィットネス・ランドスケープは、言語学習に最適な条件を創り出す一助となる。それぞれの学生は皆、文法や発音など異なるレベルのL2 スキルを保有している。これらのスキルを組み合わせることで全体的な L2 能力すなわちフィットネス・バリューを生み出すことが可能となる。このような異なるレベルの組み合わせによる全てのユニットとそれに伴うフィットネス・バリューはフィットネス・ランドスケーブ(適応度地形)を創りだす。ある L2 スキルが向上または低下する時、フィットネス・バリューは変化する。それによってランドスケープ上の位置が変化する。スキルのレベル変化を通じて学生はアダプティブ・ウォークとして知られるランドスケープを旅する。旅の到達目標は、アダプティブ・ウォークを奨励してランドスケープ上の高位のフィットネルピークを見出すことである。これらの理念の応用としていくつかの L2 アクティビティを導入する。

A Simulation of Strategic Bargainings within a Biotechnology Cluster

2007 ◽  
pp. 335-351
Author(s):  
A. Berro ◽  
I. leroux
Keyword(s):  
Local Government ◽  
Simulation Model ◽  
Complex Adaptive Systems ◽  
Artificial Life ◽  
Adaptive Systems ◽  
Local Authorities ◽  
Local Coordination ◽  
Key Players ◽  
Complex Adaptive ◽  
End Use

This chapter introduces artificial life as a means of exploring strategic relations dynamics between firms and local authorities within a local biotechnology cluster. It argues that artificial life, combined with a conception of bioclusters as complex adaptive systems, offers a significant approach to understanding the co-evolution of strategies and the potential vulnerability of such systems. The simulation model involves firms and local government administrations that negotiate to share a quasi-rent, and which, to this end, use strategies that are to a greater or lesser extent sophisticated or opportunistic. The results show that the firms adjust their bargaining strategies according to their assessment of gains which might be collectively generated. The results also bring to light that the local authorities play a regulatory role against opportunism and that they are the key players in local coordination. Stemming from these simulations, the authors develop promising new avenues of theoretical and empirical research.

EMERGENT FEATURES IN A GENERAL FOOD WEB SIMULATION: LOTKA–VOLTERRA, GAUSE'S LAW, AND THE PARADOX OF ENRICHMENT

2013 ◽  
Vol 16 (08) ◽  
pp. 1350014 ◽  
Author(s):  
TED CARMICHAEL ◽  
MIRSAD HADZIKADIC
Keyword(s):  
Simulation Model ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Marine Ecosystem ◽  
System Level ◽  
Computer Simulation Model ◽  
Agent Based ◽  
Predator Prey ◽  
Paradox Of Enrichment ◽  
Complex Adaptive

Computer simulations of complex food-webs are important tools for deepening our understanding of these systems. Yet most computer models assume, rather than generate, key system-level patterns, or use mathematical modeling approaches that make it difficult to fully account for nonlinear dynamics. In this paper, we present a computer simulation model that addresses these concerns by focusing on assumptions of agent attributes rather than agent outcomes. Our model utilizes the techniques of complex adaptive systems and agent-based modeling so that system level patterns of a marine ecosystem emerge from the interactions of thousands of individual computer agents. This methodology is validated by using this general simulation model to replicate fundamental properties of a marine ecosystem, including: (i) the predator–prey oscillations found in Lotka–Volterra; (ii) the stepped pattern of biomass accrual from resource enrichment; (iii) the Paradox of Enrichment; and (iv) Gause's Law.

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