• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.59-71
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• 2005

In this paper we address a design problem for hub and spoke transportation networks and then consider a capacitated hub locations problem with direct shipment (CHLPwD). We determine the location of hubs, the allocation of nodes to hubs, and direct shipment paths in the network, with the objective of minimizing the total cost in the network. An evolutionary algorithm is developed here to solve the CHLPwD. To do this, we propose the representation and the genetic operators suitable for the problem and adopt a heuristic method for the allocation of nodes to hubs. To enhance the search capability, problem-specific information is used in our evolutionary algorithm. The proposed algorithm is compared with the heuristic method in terms of solution quality and computation time. The experimental results show that our algorithm can provide better solutions than the heuristic.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.1
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• pp.47-55
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• 1999

This paper develops an efficient heuristic algorithm for scheduling workforce level that can accommodate all the requested maintenance jobs. Each job has its own release and due dates as well as man-day requirement, and must be scheduled in a non-interrupted time interval, namely, without preemption. Duration of each job is not fixed, but to be determined within given specific range. The objective is to minimize workforce level to complete all the requested maintenance jobs. We show that the problem can be seen as a variant of the two-dimensional bin-packing problem with some additional constraints. A non-linear mixed integer programming model for the problem is developed, and an efficient heuristic algorithm based on bin-packing algorithms is proposed. In order to evaluate goodness of the solution obtained from the proposed algorithm, a scheme for getting a good lower bound for the optimum solution is presented and analyzed. The computational experiment shows that the proposed algorithm performs quite satisfactorily.

• The KIPS Transactions:PartB
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• v.18B no.2
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• pp.73-82
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• 2011

There are a lot of people trying to solve the Traveling Salesman Problem (TSP) by using the Meta Heuristic Algorithms. TSP is an NP-Hard problem, and is used in testing search algorithms and optimization algorithms. Also TSP is one of the models of social problems. Many methods are proposed like Hybrid methods and Custom-built methods in Meta Heuristic. In this paper, we propose the S-MINE Algorithm to use the MINE Algorithm introduced in 2009 on the TSP.

• Journal of Information Processing Systems
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• v.5 no.4
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• pp.237-242
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• 2009

The classical vehicle routing problem (VRP) can be extended by including customers who want to send goods to the depot. This type of VRP is called the vehicle routing problem with pickups and deliveries (VRPPD). This study proposes a novel way to solve VRPPD by introducing a two-phase heuristic routing algorithm which consists of a clustering phase and uses the geometrical center of a cluster and route establishment phase by applying a two-way search of each route after applying the TSP algorithm on each route. Experimental results show that the suggested algorithm can generate better initial solutions for more computer-intensive meta-heuristics than other existing methods such as the giant-tour-based partitioning method or the insertion-based method.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.4
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• pp.447-456
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• 2007

The ant colony optimization (ACO) is a probabilistic Meta-heuristic algorithm which has been developed in recent years. Originally ACO was used for solving the well-known Traveling Salesperson Problem. More recently, ACO has been used to solve many difficult problems. In this paper, we develop an ant colony optimization method to solve the maximum independent set problem, which is known to be NP-hard. In this paper, we suggest a new method for local information of ACO. Parameters of the ACO algorithm are tuned by evolutionary operations which have been used in forecasting and time series analysis. To show the performance of the ACO algorithm, the set of instances from discrete mathematics and computer science (DIMACS)benchmark graphs are tested, and computational results are compared with a previously developed ACO algorithm and other heuristic algorithms.

• Journal of the Korea Society of Computer and Information
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• v.21 no.2
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• pp.71-77
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• 2016

There has been unknown polynomial time algorithm for cellular formation problem (CFP) that is one of the NP-hard problem. Therefore metaheuristic method has been applied this problem to obtain approximated solution. This paper shows the existence of polynomial-time heuristic algorithm in CFP. The proposed algorithm performs coarse-grained and fine-grained cell formation process. In coarse-grained cell formation process, the cell can be formed in accordance with machine frequently used that is the number of other products use same machine with special product. As a result, the machine can be assigned to most used cell. In fine-grained process, the product and machine are moved into other cell that has a improved grouping efficiency. For 35 experimental data, this heuristic algorithm performs better grouping efficiency for 12 data than best known of meta-heuristic methods.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2001.05a
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• pp.65-69
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• 2001

In this paper, consider the three cases of decide for appling point a general Simple Genetic Algorithm about heuristic method(Bottom and Left Sliding) at the piece auto-nesting on the row plate. The 1st case, about only using the Simple Genetic Algorithm. The 2nd case, applied the heuristic method to the genetic operating of the Simple Genetic Algorithm. The 3rd case, applied the heuristic method to the final result of the Simple Genetic Algorirhm. The estimation of final result were proceed to developed simulation program in this research.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.24 no.62
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• pp.97-109
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• 2001

This research is concerned with jobshop scheduling problem for an advanced manufacturing system like flexible manufacturing which consists of two machine centers and a single automated guided vehicle(AGV). The objective is to develop and evaluate heuristic scheduling procedures that minimize makespan to be included travel time of AGV. A new heuristic algorithm is proposed and illustrates the proposed algorithm. The heuristic algorithm is implemented for various cases by SLAM II. The results show that the proposed algorithm provides better solutions in reduction ratio and frequency than the previous algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.4
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• pp.129-137
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• 2011

To date, facility layout problems has been solved and applied for job shop situations. Since flow shop has more restrictions, the solution space is much smaller than job shop. An efficient heuristic algorithm for facility layout problems for flow shop layouts is needed to be developed. In this thesis, a heuristic algorithm for rectangular bay layouts in a flow shop situation is presented. The proposed algorithm is developed by using slicing tree representation and applied to various flow shop layout problems. The effectiveness of the proposed algorithm in terms of exploration rate and objective function value are shown by comparing our results to simulated annealing.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.8 no.11
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• pp.79-83
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• 1985

This paper is to develop four heuristic algorithms for $n/m/D/F/F_{max}$. A study present numerical example for (H1) algorithm. Among the sequence generated, the best sequence is J2, J1, J6, J7, J4, J3, J5 and makespan is 528. The optimal makespan of this numerical example can be found as 528 as also, and the worst value of heuristic solution is only 7.2 % away from it.