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Hierarchical-game based Negotiation Protocol for effective Supply Chain Network
This research focuses on the negotiation protocol between multiple Manufacture Agents (MA) and multiple Material Supplier Agents (MSA). A hierarchical-game based negotiation protocol is proposed. It is a three-layer game, where the first layer game is based on the results of the second and the third layer games. Two-person game is used to find the optimal trade partnerships to maximize the whole profit of Supply Chain Network (SCN) in the first layer. The second layer games aim to find all the possible coalitions using cooperative game. However, they are not necessary for all the time. They exist only at the situation where the order of MA exceeds the ability of MSA. Then, the third layer games are used to determine the final strategies between MAs and MSAs or all the possible coalitions found in the second layer games. Stackelberg equilibrium is introduced to resolve the conflict of the interests of the two sides. What we should pay attention to is that the second and the third layer games are nested inside the first layer game. Simulations are provided to verify the effectiveness and the feasibility of the proposed protocol. The optimal setting of the proposed protocol under given condition is obtained by the performance analysis.

Hierarchical-game based negotiation protocol


Facility Layout Planning in Central Kitchen
Central Kitchen in the food service industry is a labor-intensive workplace where preparation by hand generates additional values. Thus, the production efficiency greatly depends not only on the flow of goods but also on the flow of people. In this respect, this research aims to find the optimal facility layout based on the method which combines the Genetic Algorithm and computer simulation.

The facility layout planning by computer simulation and evolutionary computation


Optimization of Electric Power Distribution Planning of Smart Community Using Market-Oriented Programming
Recently renewable energy has attracted attention, although its power generation capacity is unstable under dynamic environment. In this respect, the smart grid technology is expected to help control power distribution. This research proposes a negotiation mechanism to derive an optimal power distribution planning in a region using the Market-Oriented Programming (MOP) which contains a multi-agent social negotiation based optimization method. Effective dynamic pricing strategy is expected by this research.

Electric power distribution planning using Market-Oriented Programming


A Solution Space Structure Based Approach of Autonomous Particle Swarm Optimization
This research aims to build a Particle Swarm Optimization (PSO) method which autonomously changes the settings for each solving problem. The structure of the solution space of an optimization problem is presumed based on the information acquired during search of the problem. According to the presumed structure, PSO parameter settings will autonomously change.

Summary of Particle Swarm Optimization


Layout Design for Underground Shopping Streets Using Agent Simulation
This research focuses on shop layout design of underground shopping streets which is considered to affect purchase behaviors. Agent simulation is applied to the shop layout design for the developers in the aim of attracting more purchasers to underground shopping streets.

Summary of agent simulation


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