Moo Hong Kang

Integration of Production and Distribution Planning Using a Genetic Algorithm in Supply Chain Management

In SCM (supply chain management), planning and operation includes the mutually related partial problems. These problems should be dealt with integrated manner on the whole aspect. The core partial problems in the SCM are production planning and distribution planning. As these problems are mutually related, they should be dealt with simultaneously in an integrated manner. This study develops a genetic algorithm that can integrate the production planning and distribution planning in the SCM.

Optimal supply chain formation using agent negotiation in a SET model-based make-to-order

In an effort to composite an optimal supply chain, this study has introduced an agent-based negotiation model as a method for assigning a lot of orders to a large number of participants. As a resources allocation mechanism to form strategic cooperation based on information sharing between supply chain members, this agent negotiation model provides such functions as bidding, scheduling, and coordination, allowing all participants to make a profit, and accomplishing a Pareto-optimum solution from the viewpoint of the whole supply chain. SET model-based scheduling takes into consideration both early (earliness) production costs and late (tardiness) production costs, along with the competitive relationship between multiple participants. This study has tried to prove that the result of an agent-based negotiation is a Pareto optimal solution under a dynamic supply chain environment, establishing the mathematical formulation for a performance test, and making a comparison with the heuristic Branch & Bound method.

Simulation analysis on effective operation of handling equipments in automated container terminal

This research aims to discover effective integrated operation method of an automated container terminal, which includes the integration of ATC re-stacking rule, AGV dispatching rule, and container crane in order to minimize the makespan in time of loading. This study tried to find out the optimal way of reducing delay time, consequently minimizing the makespan. Among the many situations – the re-marshaling degree of blocks, the number of container and AGV – an empirical study should identify which combination of operation methods are most likely to be robust and effective. To this end, simulation models of equipment operation have been tested under various environments.

Implementation of framework for developing multi-agent based automated negotiation systems

A multi-agent technology has emerged as new paradigms that can flexibly and promptly cope with various environmental changes and complex problems. Accordingly, many studies have been carried out to establish multi-agent systems in an effort to solve dynamic problems in many fields. However, most previous research on the multi-agent frameworks aimed at, on the behalf of a user, exchanging and sharing information among agents, reusing agents, and suggesting job cooperation in order to integrate and assimilate heterogeneous agents. That is, their frameworks mainly focused on the basic functions of general multi-agents. Therefore, they are not suitable to the development of the proper system for a specific field such as a negotiation. The goal of this research is to design a multi-agent framework for the negotiation system that supports the evaluation of the negotiation messages, management of the negotiation messages, and message exchanges among the negotiation agents.

Multi-agent Based Integration of Production and Distribution Planning Using Genetic Algorithm in the Supply Chain Management

Companies are pursuing a new approach through which overall functions within a supply chain, ranging from material purchase to production, distribution, and sales are designed, planned, and managed in an integrated way. The core functions among those functions are production planning and distribution planning. In this paper, we propose a multi-agent system and genetic algorithm that make it possible to integrate the production and distribution planning on a real-time basis in supply chain management.

Development of a Genetic Algorithm for the Maritime Transportation Planning of Car Carriers

Many researches have been made in order to solve global logistic problems, and especially in case of maritime transportation, much more studies have been made compared with other transportation fields because of its weight in terms of international logistics. However, little study has been made on the car carrier’s transportation, due to its relatively small weight in the maritime transportation market. For this reason, this study has tried to develop an algorithm for the maritime transportation planning of car carriers, so that they can not only reduce logistics costs but also improve competitiveness. Car carriers are usually depending upon manual work, and concerning the routing of car carriers, however, many changes are frequently taking place in the car production schedule and ship’s arrival schedule. Because of this, this study has developed a genetic algorithm for car carrier’s routing so as to make an optimal transportation planning with minimum costs. The genetic algorithm in this study has been compared with the solution results of integer programming in an effort to test its performance.

An intermodal transport network planning algorithm using dynamic programming

This paper presents a dynamic programming algorithm to draw optimal intermodal freight routing with regard to international logistics of container cargo for export and import. This study looks into the characteristics of intermodal transport using two or more modes, and presents a Weighted Constrained Shortest Path Problem (WCSPP) model. This study draws a Pareto optimal solution that can simultaneously meet two objective functions by applying the Label Setting algorithm, one of the Dynamic Programming algorithms, after setting feasible area using the objective function values drawn in the model. To improve the algorithm performance, pruning rules have also been presented. The algorithm is applied to real transport paths from Busan to Rotterdam. This study quantitatively measures the savings effect of transport cost and time by comparing single transport modes with existing intermodal transport paths. Lastly, this study applies the multiple Pareto optimal solutions drawn, to a mathematical model and MADM model, and compares the two evaluation methods as a means to evaluate the solutions.