A STUDY ON BOTTOM-UP RESOURCES CIRCULATION SYSTEMS BASED ON HIERARCHICAL MODELING

Transcription

1 A STUDY ON BOTTOM-UP RESOURCES CIRCULATION SYSTEMS BASED ON HIERARCHICAL MODELING Itsuo HATONO Information Processing Center, Kobe University Nada, Kobe , Japan Koji YOKOYAMA, Takayuki SHIOSE, and Toshiharu TAURA Graduate School of Science and Technology, Kobe University Nada, Kobe , Japan Abstract This paper deals with bottom-up resources circulation systems based on hierarchical modeling. To develop an e - cient methodology to control resources circulation systems, it is necessary to develop indirect control methods by changing the boundary condition and the constraints in the systems. In this paper, we develop a hierarchical model of a resources circulation system, which consists of two layers: a decision layer and a logistics layer. Furthermore, we analyze the change on the flow of products, parts and money in the resources circulation system by computer simulations, as the first step of developing an indirect control method. Keywords: Resources Circulation Systems, Simulation, Indirect Control, Hierarchical Modeling 1. INTRODUCTION Recently, we are facing with various environmental problems(meadows et al. 1974) as a result of the past mass production and consumption. To cope with the problems, limitations of utilization of materials whose environmental load is large, and possibilities of recycling and reuse of products are studied. However, it seems to be di cult to realize the whole resources circulation system, because almost all these studies are merely the partial improvement of the resources circulation system. Since the resources circulation systems are extremely complex and the economic environment around the system changes dynamically, it is di cult to develop a method to control the behavior. One approach to the problem is a top-down one, in which the resources circulation system is controlled the flow in that directly by governments or municipalities. An another approach is a bottom-up one, in which the system is constructed as the results of behavior of the consumers and companies based on the economic and or environmental consciousness. The former approach expects to have high controllability, but it requires enormous costs, because the resources circulation systems can be regarded as a complex system. Furthermore, it ignores the identities of the consumers and companies. The latter approach can take the identities into account, but it is not easy to construct a desirable resources circulation systems, if the behavior of the whole system assumes to be dominated by the market mechanism and the environmental consciousness of each consumer. The aim of our research is to develop a methodology for constructing and control the resources circulation system, which has the characteristics of both top-down and bottomup approaches. Therefore, we try to develop an indirect control method of the resources circulation system by changing the boundary conditions and the constraints in the system. In this paper, first, we develop a hierarchical model of a resources circulation system, which consists of two layers: a decision layer and a logistics layer, and then we analyze the influence of the decision layer on the resources circulation system constructed in the logistics layer by using the hierarchical model, as the first step of developing an indirected control method. Consumers Information Tax Government Used products Legal restriction / subsidy for recycle Mnicipality Material Products Used parts Material Manufacturer Product Manufacture Fig. 1 Conceptual illustration of indirect control by government

2 Decision layer submodel of Agent 1 Decision layer model Agent 1 Agent 2 Agent 3 Agent m Constraints Determined channel Agent 4 Logistic layer submodel of Agent 1 Logistics layer model Fig. 2 An example of a hierarchical model of a resources circulation system 2. INDIRECT CONTROL OF RESOURCES CIRCU- LATION SYSTEMS The indirect control method in this paper control resources circulation systems by changing the boundary conditions and the constraints in the system. Since the resources circulation systems are very complex and consists of many manufacturers, dealers, and consumers, each of which behaves based on market mechanisms, it is di cult to control the flow of products, materials, and money directly just like the stock market. In general, to control the such complex markets, for example, the governments impose or remove tax, legal restrictions and use subsidies, and companies advertise their products or services, and so on. Figure 1 shows a conceptual illustration of the indirect control by a government. These method does not control the flow of products and money directly, but influence the behavior of companies and consumers by changing the economic environment around those and by giving the information about the products or services. Furthermore, it is important to develop the models which describe the information flow. In resources circulation systems, it is very di cult to estimate the e ect of the recycling. For example, when consumers sell or bring the used products to manufacturers or junk dealers, the consumer can not know whether the products will be recycled actually. Moreover, there are many studies on the disasters cased by the environmental problems, each of which predicts di erent disasters each other. Therefore, in the environmental problems including resources circulation systems, it is very important to develop methodologies how the information about the environmental problems is given to consumers and companies. Moreover, there are few examples of resources circulation systems in addition to the di culties. To cope with those, we develop a hierarchical model of resources circulation systems in order to analyze the behavior. In the next section, we describes the detail of the model. 3. HIERARCHICAL MODELING OF RESOURCES CIRCULATION SYSTEMS In this paper, we develop a hierarchical model of a resources circulation system with two layers. The hierarchical model consists of agents, each of which is corresponding to an element of the resources circulation system, such as a consumer, a company, government, and so on. Furthermore, each agent consists of two layered submodels: a logistics layer submodel, which describes the flow of products or materials, and a decision layer submodel, which represents the decision making process in the agents. Each logistic and decision layer submodel belongs to a logistic and a decision layer model, respectively. Figure 2 shows a conceptual illustration of a hierarchical model. We assume that a logistics layer model describes the actual flow of the product, materials and cost between the logistic layer submodels, and each submodel has the parameters to determine its behavior such as the price of products, the cost for processing, and the environmental load of products. By using the parameters, a decision layer submodel corresponding to each logistics layer submodel decides its behavior by selecting a circulation channel. Furthermore, we also assume that the logistics layer submodels have the ability to change the parameters according to the status of the logistics layer. Figure 3 shows an example of a logistic layer model in products recycling. In the decision making processes on each decision layer submodel, we assume that an evaluation function is used for decision making and can be changed according to the status of the logistics layer submodel and the information by the interaction with the other agents. Since we can separately develop the models for the logistic layer and the decision layer in the hierarchical modeling of resources circulation systems, we can easily simulate the resources circulation systems based on various simulation scenarios and analyze the simulation results. Therefore, we hope that the hierarchical models of resources circulation

3 Recycle/Reuse Consumers Junk dealers Product manufacuturer Material Manufacturer Fig. 3 Examples of logistic layer models systems become an useful tool for developing indirect control methods. 4. A HIERARCHICAL MODEL OF THE CIRCULA- TION SYSTEM IN PC RECYCLE PROBLEM In this paper, we develop a hierarchical model of the resources circulation system for Personal Computers (PC). Figure 4 shows an example of a logistic layer model of PC recycle. In the decision layer submodel, we assume that there are no interactions between the agents in order to simplify the problem. Each agent except consumer agents determines its behavior by using three kinds of parameters: price, workload for processing, and environmental load of the products or material. 4.1 Decision layer model except consumers In this paper, price P of a product or a material is determined by using the equation as follows; P C M (1) C C 1 N C 2 (2) where C C 1 C 2 N, and M denote a total cost, fixed cost, fluctuation cost, volume in a unit time, and profitability, respectively. Let M n, N n be a profitability at time n and the volume of products processed at time n. In this paper, profitability M is also changed according to the volume by using the equation as follow: M n M n 1 (N N N (n 1) ) b (3) where b is a constant to describe the variation rate of profitability. The value of each parameter is described in an integer from 1 to 10 by translating from the actual value to the utility value(keeney and Rai a 1976). In this paper, only the price of each product can be changed according to to the volume, the fixed constant, and the profitability to simplify the problem. In the decision layer submodel of each agent, a circulation channel is selected based on the parameters assigned to the logistics layer submodel and the weights which describe the value of each agent. In this paper, each agent selects an agent for the circulation channel whose value H in equation (4) is largest. H w 1 u P w 2 u L w 3 u E (w 1 w 2 w 3 1) (4) where L and E denote a workload and an environmental load, respectively. In this paper, we assume that each parameter w 1, w 2, and w 3 is fixed. 4.2 Decision layer model of consumers In this paper, we assume that each consumer determines its behavior based on three kind of attributes: cost to recycling PCs, troublesomeness of recycling, the interests on the protection of the environment. Each consumer determines a circulation channel by using the equation as follows: H c w c 1 uc P wc 2 uc T wc 2 uc I (wc 1 wc 2 wc 3 1) (5) where u c P, uc T, and uc I denote the utility value of cost to recycling PCs, troublesomeness of recycling, and the interests on the protection of the environment. H c denotes an utility value of the circulation channel whose utility of the attributes are u c P, uc T, and uc I, respectively. Furthermore, we also describe the utility value for each attribute as an integer from 1 to SIMULATION EXAMPLES 5.1 Simulation results with the fixed weights We develop a simulation program in order to evaluate the model of the resources circulation system of PC recycle. In this model, we assume that the utility value of the workload for processing of each agent is small in order of retail stores, junk dealers, municipalities, and manufacturers, and the environmental load of disposal is much larger than those of other agents. Furthermore, we also assume that the decision makers corresponding to each agent can be classified

4 Consumer Flow of PC Flow of Parts Flow of Material Manufacturer Disassembly Company Gold Manufacturer Plastic Manufacturer Steel Manufacturer Glass Manufacturer Copper Manufacturer Dealer of Used PC PC Used PC Used parts Material Fig. 4 An example of a logistic layer model of the circulation system in PC recycle Table 1 Parameters in decision layer model except consumers Agent Workload Environmental load Retail store 7 10 Junk dealer 5 10 Municipality 3 10 Manufacture into four types: people who are interested in environmental problems, people who dislike troublesome tasks, people who emphasis on money, and people who has same weights on each evaluation item. Table 1 and 2 show the values of the parameters assigned to the agents. Figure 5 shows the simulation results. Each line in Fig. 5 represents the amount of the flow in every 20 unit time to retail stores, junk dealers, municipalities, and manufactures, and disposal, respectively. In this result, the amount of the flow to the retail stores and the municipalities does not converge, but are oscillating. In the simulation result in the different conditions, we observed that those flows converge. These result suggests that the flows in resources circulation systems are sensitive to the parameters and the weights of Table 2 Parameters in decision layer model of consumers (1) Type of consumer w 1 w 2 w 3 Type Type Type Type each agent. We use Arena(Kelton et al. 1988) TM to simulate the whole models. 5.2 Simulation results with the variable weights In this simulation, we assume that each consumer determines the behavior by using the equation as follows: H c w c 1 up w c 2 ui (w 1 w 2 1) (6) where u p and u I denote the utility value of cost to recycling PCs and the interests in the protection of the environment. Furthermore, we also assume that w c 1 and wc 2 in equation (6) are updated by using equation (7) and (8), when the information about the e ect of recycling is given to a consumer. w c 1 w c 1 ( 0 1 w c 2 0 1) (7) w c 2 w c 2 ( 0 1 w c 2 0 1) (8)

5 Volume of processed PCs per 20 time unit Manufactureres Simulation time Fig. 5 Simulation result of the flow in the logistics layer model Table 3 Parameters in decision layer model of consumers (2) Type of consumer w 1 w 2 Type Type Type where if w p 1 and w p 2 are greater than 1, then let w p 1 and w p 2 be 1, respectively. In this simulation, we assume that the decision makers corresponding to each agent can be classified into three types: people who emphasis on environmental problems, people who emphasis on money, and people who has about same weights on each evaluation item. Table 3 shows the initial values of w c 1 and wc 2. Figure 6 shows a simulation result when each consumer is not be informed about the e ect of recycling. In Fig. 6, the number of disposed PCs increases after 300 time step, and there are very few flows to retail stores and municipalities. Figure 7 show the simulation results when each consumer is informed whether the number of disposed PCs in every 20 time step increases or not. In Fig. 7, the number of disposed PCs is much less than that in Fig. 6. This simulation results suggest it has possibility to decrease the amount of disposed PCs by informing the e ect of recycling. 6. CONCLUSION AND FUTURE REMARKS In this paper, we proposed a hierarchical modeling of bottom-up resources circulation systems in order to develop an e cient methodology for constructing and controlling the resources circulation system. Furthermore, we develop a hierarchical model of a PC recycle system and analyze the simulation results of the model to evaluate the e ciency of that. Further research might be focused on the development of more detailed model and an indirected control method of resources circulation systems by combining the other theories, such as control theories and discrete event theories. Acknowledgement The authors would like to thank Mr. K. Ohta of Kobe University for his assistance to the simulation studies in this paper. References Keeney, R.L. and H. Rai a (1976). Decisions with Multiple Objectives: Preferences and Value Tradeo s. John Wiley and Sons. Kelton, W.D., R.P. Sadowski and D.A. Sadowski (1988). Simulation with Arena. McGraw-Hill. Meadows, D. L., W. W. Behrens III, D. H. Meadows, R. F. Naill, J. Randers and E. K. O. Zahn (1974). Dynamics of Growth in a Finite World. Productivity Press, Cambridge MA.

6 Volume of processed PCs per 20 unit time Manufactureres Simulation time Fig. 6 Simulation result when each consumer is not informed about the e ect of recycling Volume of processed PCs per 20 unit time Manufactureres Simulation time Fig. 7 Simulation result when each consumer is informed about the e ect of recycling