Market-oriented Programming Research Articles

Protectionism vs. Non-Interventionism: Two Approaches to Media Diversity in Commercial Terrestrial Television Regulation

Roughly a decade has now passed since the full-scale introduction of digital terrestrial television (DTTV) across the European continent. In Scandinavia, DTTV put an end to the so-called duopolistic television market model, in which a fee-financed public service broadcaster (PSB) competed with a commercial, but carefully regulated, broadcaster—a hybrid. The hybrid concept was an attempt to maintain a diverse broadcasting market also in small linguistic markets. Building on the theoretical framework of market failure, this article compares the impact on external and internal market pluralism of the protectionist policy of Norway, which has chosen to keep a hybrid channel also in the new multi-channel environment, and the non-interventionist policy of Sweden, in which the hybrid concept has been abandoned. The results point to a problematic trade-off, where the more public service-oriented Norwegian hybrid TV2 has experienced plummeting market shares, whereas the Swedish “former-hybrid” TV4—following a clear reorientation towards more market-oriented programming—has been able to uphold theirs. The findings highlight the increasing difficulties of designing effective national media policies in the globalised media landscape.

A Proposal of Economic Negotiation Mechanism with a Complex Network for Supply Chain Management

Virtual market based supply chain operations solve product allocation problems by distributing scheduled resources according to market prices, which define the common scale of value across various products. We formulate the supply chain model as a discr ete resource allocation problem, and propose an economic negotiation mechanism with a market-oriented programming framework based on complex network information topology. Heterogeneous agents of three types are defined in the virtual market. Their interactions with micro-behaviour show a macro order of the virtual market via a complex network. The clearing price dynamism can be analysed in economic terms. The applicability of the framework to a resource allocation problem for supply chain management is also discussed.

On Energy Trading Decision Methods in Distributed Energy Management Systems with Multiple Customers

This paper addresses an operation and energy purchase planning problem under the CO2 emissions regulation for corporate entities. Considering energy trading, more efficient energy consumption may be possible. We have studied an agent-based planning system, called Distributed Energy Management Systems (DEMSs), which intends to reduce energy consumption. In the DEMSs, CO2 emissions regulation is imposed on each corporate entity, and electrical and thermal energy trading among the entities are allowed. We have proposed an energy trading decision method based on the Market Oriented Programming (MOP). In this paper, we propose trading decision methods for the group composed of several customers and several suppliers. Experimental results show effectiveness of the proposed method.

A Study on Market-based Strategic Procurement Planning in Convergent Supply Networks

We present a market-based decentralized approach which uses a market-oriented programming algorithm to obtain Pareto-optimal allocation of resources traded among agents which represent enterprise units in a supply network. The proposed method divides the network into a series of Walrsian markets in order to obtain procurement budgets for enterprises in the network. An interaction protocol based on market value propagation is constructed to coordinate the flow of resources across the network layers. The method mitigates the effect of product complementarity in convergent network by allowing for enterprises to hold private valuations of resources in the markets.

An Energy Distribution Decision Method in Distributed Energy Management Systems with Several Agents

The need to control CO2 emissions, which are the main factor of global warming, is one of the most important problems in the 21st century. Therefore, the efficient supply and use of energy are indispensable. We have studied distributed energy management systems (DEMSs), in which we target to optimal plans that minimize costs through electrical and thermal energy trading under CO2 emissions regulation. Previously, a trading method in which the Market Oriented Programming (MOP) is applied to DEMSs was proposed. However, this trading method can be used in the DEMSs consisted of a single consumer and several producers. In this paper, extending this method, we propose a trading method that can be used in DEMSs which consist of several consumers and several producers. Experimental results show that the method is effective in the DEMSs with several consumers and several producers.

An Application of the Market-Oriented Programming to Energy Trading Decision Method in Distributed Energy Management Systems

A control of CO2 emissions which is the main factor of global warming is one of the most important problems in the 21st century about preservation of earth environment. Therefore, efficient supply and use of energy are indispensable. We have proposed distributed energy management systems (DEMSs), where we are to obtain optimal plans that minimize both of costs and CO2 emissions through electrical and thermal energy trading. A DEMS consists of the plural entities that seek their own economic profits. In this paper, we propose a trading method that gives competitive equilibrium resource distribution by applying the market-oriented programming (MOP) to DEMSs.

A multiagent-based complex systems approach for dynamic negotiation mechanism in virtual enterprise

Nowadays a sophisticated match-making mechanism is necessary for appropriate collaborations in virtual enterprise (VE). Virtual market based match-making operation enables effective partner search in terms of products allocation by distributing the scheduled resources according to the market prices, which define common scale of value across the various products. We formulate the VE match-making model as discrete resource allocation problem, and propose a complex market-oriented programming framework based on the economics of complex systems. Three types of heterogeneous agents are defined in the complex virtual market. It is described that their interactions with micro behaviour emerge a macro order of the virtual market, and the clearing price dynamism can be analysed in economic terms. The applicability of the framework into resource allocation problem for VE is also discussed.

4201 完全競争市場下における市場指向プログラミングの単一工程並列機械生産スケジューリング問題への適用(OS4 環境適応型知的人工システム)

4201 完全競争市場下における市場指向プログラミングの単一工程並列機械生産スケジューリング問題への適用(OS4 環境適応型知的人工システム)

A study on resource allocation with buying behavior in B to B commerce

B to B commerce is an important research issue for increasing the profitability in global markets. Sophisticated B to B commerce requires optimality in resource allocation based on the human behavior dynamism. A market-oriented programming calculates a Pareto-optimal resource allocation in the market by computing competitive equilibrium of an artificial economy. In this paper we propose a new resource allocation algorithm based on market-oriented programming, which takes into account the consumers' buying behavior influencing the B to B commerce. According to this method, supply agents in the computational market decide their supply plan by estimating the demand agents' behavior. Careful constructions of the agents according to the buying behavior can lead to an efficient allocation of distributed resources, and the behavior of the agents can be analyzed in economic terms. © 2005 Wiley Periodicals, Inc. Electr Eng Jpn, 153(1): 63–72, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20060

Autonomic computing approach for resource allocation

Abstract This paper presents an autonomic solution based in a multi-agent model for resource allocation in a manufacturing environment. This model considers the temporal and synchronism aspects involved in the allocation process. To attend to this purpose a framework was developed with a CIMOSA compliant architecture. To support the framework four agents where defined: the Domain Process Agents (DPA), the Business Process Agents (BPA), the Enterprise Activity Agents (EAA) and the Functional Entity Agents (FEA). Planning networks are used as a strategy to manage the scheduling process complexity. The main contributions of this work are: (i) a user-independent framework allowing to manage the intrinsic scheduling complexity, (ii) a strategy for resource planning allocation based on a multi-agent paradigm including a major complexity element: the real-time disturbances, (iii) the use of multi-agent architecture to support this strategy. The agents' interaction is obtained using the contract net algorithm and market-oriented programming.

A Study on Resource Allocation with Buying Behaviour in B to B Commerce

B to B commerce is an important research issue for increasing profitability in global market. A sophisticated B to B commerce requires optimality in resource allocation with human behaviour dynamism. A market-oriented programming calculates a Pareto-optimal resource allocation in the market by computing competitive equilibrium of an artificial economy. In this paper we newly propose a resource allocation algorithm based on market-oriented programming with consumers buying behaviour for B to B commerce. Supply agents in the computational market decide their supply plan by estimating the demand agents’ behaviour in this method. Careful constructions of the agents according to the buying behaviour can lead to efficient distributed resource allocation, and the behaviour of the agents can be analysed in economic terms.

不完全競争市場における市場指向プログラミングの特性評価 : 完全競争市場との比較(環境適応型知的人工システム)

不完全競争市場における市場指向プログラミングの特性評価 : 完全競争市場との比較(環境適応型知的人工システム)

A study on virtual market model for e-Marketplace server

Internet procurement is now in progress and is regarded as an information infrastructure for global business. As the number and diversity of EC (electronic commerce) participants grows at the agile environment, the complexity of purchasing from a vast and dynamic array of goods and services needs to be hidden from the end user. Putting the complexity into the EC system instead means providing flexible auction server for enabling commerce within different business units. Market mechanism could solve the product distribution problem in the auction server by allocating the scheduled resources according to market prices. In this paper, we propose an e-Marketplace server for B2B EC with multi-agent paradigm, named market-oriented programming, that mediates amongst unspecified various companies in the trade, and demonstrate the applicability of the economic analysis to this framework. The proposed server facilitates a sophisticated e-Marketplace, which conducts a Pareto optimal solution for all the participating business units, in the coming agile era.

Adaptation and Learning of Agents in Market Oriented Programming

Market Oriented Programming (MOP) proposed by Wellman is a decentralized control method using auction machanism inspired by the market economy. It is applied to many problems such as network and computation resource allocation. Conventional MOP models are formulated based on the concept of ‘competitive market’ of economics which assumes that the market consists of sufficiently many and small agents. However, in realistic applications of MOP, number of agents is limited and their interdependency is not negligible. In this paper, MOP for interdependent agents is discussed. An oligopoly market model for MOP is introduced, and adaptation process of interdependent agents and its stability are discussed. Further, it is also demonstrated that selfish learning of adaptation coefficiency by each agent achieves stability of market through computer simulation.

A Study on Partnering Mechanism in B to B EC Server for Global Supply Chain Management.

B to B Electronic Commerce (EC) technology is now in progress and regarded as an information infrastructure for global business. As the number and diversity of EC participants grows at the agile environment, the complexity of purchasing from a vast and dynamic array of goods and services needs to be hidden from the end user. Putting the complexity into the EC system instead means providing flexible auction server for enabling commerce within different business units. Market mechanism could solve the product distribution problem in the auction server by allocating the scheduled resources according to market prices. In this paper, we propose a partnering mechanism for B to B EC with market-oriented programming that mediates amongst unspecified various companies in the trade, and demonstrate the applicability of the economic analysis to this framework after constructing a primitive EC server. The proposed mechanism facilitates sophisticated B to B EC, which conducts a Pareto optimal solution for all the participating business units in the coming agile era.

4111 市場指向プログラミングによるワルラス型仮想市場の構築

In our economic society, the market serves as the mechanism for decentralized resource allocation. In the disciplinary of neoclassical economics, the fundamental theorem of welfare economics vouchs the Pareto optimality of the equilibrium allocation in Walrasian market. In this paper, we develop Walrasian virtual market with Market-Oriented Programming based on multi-agent paradigm, and validate on Pareto optimality of the allocation in the market by comparing with analytical methods.

Agent Strategy and Resource Allocation Dynamism on Market-Oriented Programming-Basic Analysis

Market-oriented programming is a multi-agent-based concept to facilitate distributed problem solving. In market-oriented programming we take the metaphor of an economy computing multiagent behaviour literally, and directly implement the distributed computation as a market price system. In a market-oriented programming approach to distributed problem solving, the resource allocation for a set of computational agents is derived by computing competitive market of an artificial economy. Since heterogeneous agent strategies have intensive effects on the resource allocation, dynamism, we analyse and systematise their relationship in supply chain simulation with a virtual market.The behaviour of the system can be analysed in agent interactions based on economic strategies.

Supply chain management with market economics

Supply chain management (SCM) is now recognised as one of the best means by which enterprises can make instant improvements to their business strategies and operations. SCM, however, is generally based on the simple theory of constraints (TOC) concept, and is not always concerned with Pareto optimal solutions in product distribution. Since market price systems constitute a well-understood class of mechanisms that under certain conditions provide effective decentralisation of decision making with minimal communication overhead, we propose SCM based on market-oriented programming in this paper. In market-oriented programming, we take a metaphor of economy computing multi-agent behaviour literally, and directly implement the distributed computation as a market price system. We define the agent activities to negotiate the tradeoffs of acquiring different resources, so as to realise the multi-echelon optimisation. Several simulation experiments on the supply chain model with multi-echelon structure clarify the market dynamics that emerge through the agent negotiations. It is confirmed that careful constructions of the decision process according to economic principles can lead to Pareto optimal resource allocations in SCM, and the behaviour of the system can be analysed in economic terms.

107 仮想市場型サプライチェーンにおけるエージェントの戦略と資源配分特性(OS-5 生産システム)

Market-oriented programming is a multi-agent-based concept to facilitate distributed problem solving. In market-oriented programming we take the metaphor of an economy computing multi-agent behaviour literally, and directly implement the distributed computation as a market price system. In a market-oriented programming approach to distributed problem solving, the resource allocation for a set of computational agents is derived by computing competitive market of an artificial economy. Since heterogeneous agent strategies have intensive effects on the resource allocation dynamism, we analyse and systematise their relationship in supply chain simulation with virtual market.

納期効用を含んだ市場指向プログラミングに関する研究

納期効用を含んだ市場指向プログラミングに関する研究