Integrated urban evolutionary modeling

Cellular automata models have proved rather popular as frameworks for simulating the physical growth of cities. Yet their brief history has been marked by a lack of application to real policy contexts, notwithstanding their obvious relevance to topical problems such as urban sprawl. Traditional urban models which emphasize transportation and demography continue to prevail despite their limitations in simulating realistic urban dynamics. To make progress, it is necessary to link CA models to these more traditional forms, focusing on the explicit simulation of the socio-economic attributes of land use activities as well as spatial interaction. There are several ways of tackling this but all are based on integration using various forms of strong and loose coupling which enable generically different models to be connected. Such integration covers many different features of urban simulation from data and software integration to internet operation, from interposing demand with the supply of urban land to enabling growth, location, and distributive mechanisms within such models to be reconciled. Here we will focus on developin

Decision support for build-to-order supply chain management through multiobjective optimization

This is the post-print version of the final paper published in International Journal of Production Economics. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.This paper aims to identify the gaps in decision-making support based on multiobjective optimization (MOO) for build-to-order supply chain management (BTO-SCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting MOO techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted. Future research directions to better exploit the decision support capabilities of MOO are proposed. These include: reformulation of the extant optimization models with a MOO perspective, development of decision supports for interfaces not involving manufacturers, development of scenarios around service-based objectives, development of efficient solution tools, considering the interests of each supply chain party as a separate objective to account for fair treatment of their requirements, and applying the existing methodologies on real-life data sets.Brunel Research Initiative and Enterprise Fund (BRIEF

Decision support for build-to-order supply chain management through multiobjective optimization

This paper aims to identify the gaps in decision-making support based on multiobjective optimization for build-to-order supply chain management (BTOSCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting multiobjective optimization (MOO) techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted and future research directions to better exploit the decision support capabilities of MOO are proposed

Налоговое или монетарное стимулирование? Эволюционные аргументы в пользу налоговых реформ

Статья посвящена исследованию проблемы обоснования мер регулирования развития эмерджентной экономики - фискальных и (или) монетарных, с использованием методов эволюционного моделирования. Для этого была построена экономико-математическая модель, имитирующая процессы коэволюции развитой и развивающейся стран, связанных через глобальные цепочки создания стоимости. В этой модели каждая из стран характеризуется собственной исходной структурой экономических субъектов, определяемой соотношением предприятий-эгоистов (предрасположенных к консервативному поведению) и предприятий-альтруистов (предрасположенных к инновационному поведению), а также специфическим населением и демографическими процессами. Результаты вычислительных экспериментов показали, что успех того или иного способа экономического регулирования принципиально зависит от особенностей исходного состояния институциональной среды хозяйствования. В институциональной среде с «прозрачными» длинными правилами игры и, соответственно, длинным горизонтом хозяйственного планирования наилучший результат в виде высоких темпов роста производства в эмерджентной экономике дает политика дешевых денег в сочетании с высокими «европейскими» налогами. Иная ситуация наблюдается в более реалистичной ситуации с короткими правилами игры и, соответственно, коротким (не более 5 лет) горизонтом хозяйственного планирования. В этом случае любая налоговая политика (низкие или высокие налоги) в сочетании любыми деньгами (дешевыми или дорогими), в определенном смысле теряет значение, поскольку изначально отсталая инновационная система не позволяет быстро получать высокие результаты, а преимущества экономического роста в отделенном будущем не принимаются во внимание. Вместе с тем, для постепенного формирования лучшей инновационной системы низкие налоги и дешевые деньги имеют важное значение, поскольку создают лучшие условия для выживания предприятийальтруистов, облегчая им инвестиционную деятельность, способную принести многократный прирост технической производительности и экономической эффективности. В любом случае, в контексте эволюционной экономической теории, исходя из проведенных вычислительных экспериментов, налоговая политика в условиях эмерджентных рынков сохраняет свой регуляторный потенциал, и, таким образом, требует дальнейшего реформирования в контексте «новой реальности», основанной на глобальных цепочках создания стоимости.The article deals with the problem of substantiation of the emergent economies development regulatory measures (fiscal and / or monetary), using the evolutionary modelling methods. For this purpose, the mathematical model was constructed that simulates the co-evolution process of the advanced and developing countries, linked by global value chains. In this model, each country is characterized by its original structure of economic entities, defined by the ratio of the egoistic enterprises (predisposed to conservative behaviour) to the altruistic enterprises (predisposed to innovation), as well as by specific population and demographic processes. The results of the computational experiments have shown that the success of economic regulation fundamentally depends on the peculiarities of the initial state of the institutional environment. In the institutional environment with the «transparent» long behaviour and, accordingly, a long economic planning horizon, the best result in the form of average annual production growth rate of the emergent economies is provided by the cheap money policy combined with the high European taxes. A different situation is observed in more realistic short behaviour and, accordingly, short (under 5 years) economic planning horizon. In this case, any tax policy (neither low nor high taxes) together with any money (neither cheap nor expensive), to a certain extent loses its significance, as the initially backward innovative system does not allow to quickly get good results, and the long-term benefits of the potential economic growth are not taken into consideration. However, low taxes and cheap money are important as they create better conditions for survival of the altruistic enterprises, facilitating their investment activities, which can multiply increase their technical performance and economic efficiency. Still, in the context of the evolutionary economics and following the conducted computational experiments, the fiscal policy in terms of emerging markets retains its regulatory capacity, and therefore requires further reforms in the context of the «new reality» based on the global value chains

A framework for the simulation of structural software evolution

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2008 ACM.As functionality is added to an aging piece of software, its original design and structure will tend to erode. This can lead to high coupling, low cohesion and other undesirable effects associated with spaghetti architectures. The underlying forces that cause such degradation have been the subject of much research. However, progress in this field is slow, as its complexity makes it difficult to isolate the causal flows leading to these effects. This is further complicated by the difficulty of generating enough empirical data, in sufficient quantity, and attributing such data to specific points in the causal chain. This article describes a framework for simulating the structural evolution of software. A complete simulation model is built by incrementally adding modules to the framework, each of which contributes an individual evolutionary effect. These effects are then combined to form a multifaceted simulation that evolves a fictitious code base in a manner approximating real-world behavior. We describe the underlying principles and structures of our framework from a theoretical and user perspective; a validation of a simple set of evolutionary parameters is then provided and three empirical software studies generated from open-source software (OSS) are used to support claims and generated results. The research illustrates how simulation can be used to investigate a complex and under-researched area of the development cycle. It also shows the value of incorporating certain human traits into a simulation—factors that, in real-world system development, can significantly influence evolutionary structures

An evolutionary complex systems decision-support tool for the management of operations

Purpose - The purpose of this is to add both to the development of complex systems thinking in the subject area of operations and production management and to the limited number of applications of computational models and simulations from the science of complex systems. The latter potentially offer helpful decision-support tools for operations and production managers. Design/methodology/approach - A mechanical engineering firm was used as a case study where a combined qualitative and quantitative methodological approach was employed to extract the required data from four senior managers. Company performance measures as well as firm technologies, practices and policies, and their relation and interaction with one another, were elicited. The data were subjected to an evolutionary complex systems (ECS) model resulting in a series of simulations. Findings - The findings highlighted the effects of the diversity in management decision making on the firm's evolutionary trajectory. The CEO appeared to have the most balanced view of the firm, closely followed by the marketing and research and development managers. The manufacturing manager's responses led to the most extreme evolutionary trajectory where the integrity of the entire firm came into question particularly when considering how employees were utilised. Research limitations/implications - By drawing directly from the opinions and views of managers, rather than from logical "if-then" rules and averaged mathematical representations of agents that characterise agent-based and other self-organisational models, this work builds on previous applications by capturing a micro-level description of diversity that has been problematical both in theory and application. Practical implications - This approach can be used as a decision-support tool for operations and other managers providing a forum with which to explore: the strengths, weaknesses and consequences of different decision-making capacities within the firm; the introduction of new manufacturing technologies, practices and policies; and the different evolutionary trajectories that a firm can take. Originality/value - With the inclusion of "micro-diversity", ECS modelling moves beyond the self-organisational models that populate the literature but has not as yet produced a great many practical simulation results. This work is a step in that direction

Evolutionary Algorithms for Reinforcement Learning

There are two distinct approaches to solving reinforcement learning problems, namely, searching in value function space and searching in policy space. Temporal difference methods and evolutionary algorithms are well-known examples of these approaches. Kaelbling, Littman and Moore recently provided an informative survey of temporal difference methods. This article focuses on the application of evolutionary algorithms to the reinforcement learning problem, emphasizing alternative policy representations, credit assignment methods, and problem-specific genetic operators. Strengths and weaknesses of the evolutionary approach to reinforcement learning are presented, along with a survey of representative applications

CAST – City analysis simulation tool: an integrated model of land use, population, transport and economics

The paper reports on research into city modelling based on principles of Science of Complexity. It focuses on integration of major processes in cities, such as economics, land use, transport and population movement. This is achieved using an extended Cellular Automata model, which allows cells to form networks, and operate on individual financial budgets. There are 22 cell types with individual processes in them. The formation of networks is based on supply and demand mechanisms for products, skills, accommodation, and services. Demand for transport is obtained as an emergent property of the system resulting from the network connectivity and relevant economic mechanisms. Population movement is a consequence of mechanisms in the housing and skill markets. Income and expenditure of cells are self-regulated through market mechanisms and changing patterns of land use are a consequence of collective interaction of all mechanisms in the model, which are integrated through emergence

Futures Studies in the Interactive Society

This book consists of papers which were prepared within the framework of the research project (No. T 048539) entitled Futures Studies in the Interactive Society (project leader: Éva Hideg) and funded by the Hungarian Scientific Research Fund (OTKA) between 2005 and 2009. Some discuss the theoretical and methodological questions of futures studies and foresight; others present new approaches to or procedures of certain questions which are very important and topical from the perspective of forecast and foresight practice. Each study was conducted in pursuit of improvement in futures fields

From Social Simulation to Integrative System Design

As the recent financial crisis showed, today there is a strong need to gain "ecological perspective" of all relevant interactions in socio-economic-techno-environmental systems. For this, we suggested to set-up a network of Centers for integrative systems design, which shall be able to run all potentially relevant scenarios, identify causality chains, explore feedback and cascading effects for a number of model variants, and determine the reliability of their implications (given the validity of the underlying models). They will be able to detect possible negative side effect of policy decisions, before they occur. The Centers belonging to this network of Integrative Systems Design Centers would be focused on a particular field, but they would be part of an attempt to eventually cover all relevant areas of society and economy and integrate them within a "Living Earth Simulator". The results of all research activities of such Centers would be turned into informative input for political Decision Arenas. For example, Crisis Observatories (for financial instabilities, shortages of resources, environmental change, conflict, spreading of diseases, etc.) would be connected with such Decision Arenas for the purpose of visualization, in order to make complex interdependencies understandable to scientists, decision-makers, and the general public.Comment: 34 pages, Visioneer White Paper, see http://www.visioneer.ethz.c