Suk-Jae Jeong

The efficient search method of simulated annealing using fuzzy logic controller

Simulated annealing method has been successfully applied to various combinatorial optimization problems. In the conventional simulated annealing, temperature and local search repetition are determined by simple algorithms with a higher transition probability in the beginning of the search and lower probability toward the end of the search. But these simple methods can cause inefficient search process. In order to overcome this defect, this paper provides an adaptive simulated annealing algorithm using fuzzy logic controller (FLC). FLC can control the temperature and the local search repetition of simulated annealing, thereby making the search process of simulated annealing more efficient. The performance of the proposed method is evaluated and favorably compared with the conventional simulated annealing through traveling salesman problem and equal piles problem.

Adaptive Response Mechanism Based on the Hybrid Simulation and Optimization for the Real Time Event Management

Implementing the effective and efficient planning methods is a critical means to gain competitiveness for the decision-maker of manufacturing enterprise in today’s global market. We proposed adaptive response mechanism based on the hybrid simulation and optimization (ARESOP) that provides a formal bridge between long-term plans and short-term schedules. ARESOP is composed of Knowledge Generator (KG) based optimization mechanism and Knowledge Simulator (KS) based discrete event system and performance monitor based rule-based heuristic mechanism. The KG selects the optimal plan of control parameters based on the estimated behavior of the system and forecasting demand from legacy system like ERP and MRP. The KS evaluate the plan from KS and check whether it is acceptable. Feedback control loops are employed at higher level to evaluate the performance and update the control parameters. Also, The comparison between the optimal and actual values of the two monitoring variables: demand and production release rates is performed by Performance Monitor (PM) module. The times at which performance monitoring is done can be periodic (performance is sampled at regular time intervals, event-based (performance is sampled upon detection of certain event such as machine breakdown, urgent order arrivals). The significant advantage of the proposed method is shown. For a design and implementation, the data model and architecture of ARESOP is presented in this paper.

School Bus Routing Problem with Mixed-Load and Dynamic Arrivals

The School Bus Routing Problem(SBRP) seeks to plan an efficient schedule of a fleet of school buses that must pick up student from various bus stops and deliver them by satisfying various constraints; maximum capacity of the bus, maximum riding time of students, arrival time between a school`s time window. By extending the existing SBRP, we consider a case study of SBRP with allowance of mixed-loading and dynamic arrivals reflecting the school bus operation of university in Korea. Our solution procedure is based on constructing the initial solution using sweep algorithm and then improving solution within the framework of the evolutionary approach known as efficient meta-heuristics. By comparing the various scenarios through the constraints relaxation for reflecting the real operational strategies, we assess the merit of our proposed procedure.