• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.319-322
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• 2004

물류/택배업계의 공급사슬관리에서 차량에 의한 고객의 요구 서비스 시간대 만족은 고객의 재고수준을 낮추고 또한 서비스 수준의 향상에 매우 중요한 제약조건이다. 최근에 소개된 메타휴리스틱인 개미해법(Ant Colony Optimization: ACO)은 NP-hard 문제의 해공간 탐색에 있어서 상당한 장점을 가지고 있으나, 시간대 제약이 있는 차량경로문제(Vehicle Routing Problems with Time Windows: VRPTW)에 대한 적용은 아주 미비한 실정이다. 따라서, 본 연구에서는 ACO 를 VRPTW에 적용하여 최선의 차량경로 해를 구하기 위한 여러 변형을 제시하고, 이들의 영향을 다양한 실험문제를 이용하여 분석하고자 한다. 계산실험 결과, 기본 ACO 에 여러 설계 요소들을 추가함에 따라 계산시간이 다소 증가하지만 보다 우수한 차량경로 해를 구할 수 있었다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.311-314
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• 2004

The 2 DBPP(Two-Dimensional Bin Packing Problem) is a problem of packing each item into a bin so that no two items overlap and the number of required bins is minimized under the set of rectangular items which may not be rotated and an unlimited number of identical rectangular bins. The 2 DBPP is strongly NP-hard and finds many practical applications in industry. In this paper we discuss a tabu search approach which includes tabu list, intensifying and diversification strategies. The HNFDH(Hybrid Next Fit Decreasing Height) algorithm is used as an internal algorithm. We find that use of the proper parameter and function such as maximum number of tabu list and space utilization function yields a good solution in a reduced time. We present a tabu search algorithm and its performance through extensive computational experiments.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.773-774
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• 2005

The knapsack problem (KP) is one of the traditional optimization problems. Specially, multiconstrained knapsack problem (MKP) is well-known NP-hard problem. Many heuristic algorithms and evolutionary algorithms have tackled this problem and shown good performance. This paper presents a novel genetic algorithm for the multiconstrained knapsack problem. The proposed algorithm is called 'Adaptive Link Adjustment'. It is based on integer random key representation and uses additional ${\alpha}$ and ${\beta}$-process as well as selection, crossover and mutation. The experiment results show that it can be archive good performance.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04a
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• pp.19-21
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• 2002

우리는 저전력 소모를 위한 상위 수준(high-level)에서의 효과적인 바인딩(binding) 알고리즘을 제안한다. 이전 연구들에 의해서 저전력 소모를 위한 몇몇의 바인딩 알고리즘들은 멀티-코모도티 플로우(multi-commodity flow) 문제로 모델링 될 수 있음이 밝혀졌다. 그러나 멀티-코모도티 플로우 문제는 NP-hard이기 때문에 진은 크기의 설계에만 적용될 수 있다. 이러한 제약을 극복하기 위해 우리는 네트워크 상의 플로우를 잘 이용해서 효과적으로 빠른 시간 안에 최적에 가까운 결과를 낼 수 있는 방법을 제안하여 크기가 큰 설계에도 적용할 수 있도록 한다. 이를 위해 우리는 첫번째 단계에서는 네트워크에서 최소 비용의 최대 플로우 (maximum f1ow -minimum cost)를 구하는 방법을 부분적으로 이용해서 유효한 결과를 구하고 두 번째 단계에서는 이를 반복적으로 개선시켜나가는 2 단계의 알고리즘을 제안한다. 벤치마크를 이용한 실험 결과는 제안된 알고리즘이 실제적인 설계에 적용되었을때, 충분히 빠른 시간 안에 최적에 가까운 결과를 생성함을 보여준다.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.53 no.4
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• pp.210-215
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• 2004

This paper proposes an implicit method for computing the minimum cost feedback vertex set for a graph. For an arbitrary graph, a Boolean function is derived, whose satisfying assignments directly correspond to feedback vertex sets of the graph. Importantly, cycles in the graph are never explicitly enumerated, but rather, are captured implicitly in this Boolean function. This function is then used to determine the minimum cost feedback vertex set. Even though computing the minimum cost satisfying assignment for a Boolean function remains an NP-hard problem, it is possible to exploit the advances made in the area of Boolean function representation in logic synthesis to tackle this problem efficiently in practice for even reasonably large sized graphs. The algorithm has obvious application in flip-flop selection for partial scan. The algorithm proposed in this paper is the first to obtain the MFVS solutions for many benchmark circuits.

• IE interfaces
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• v.18 no.4
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• pp.504-511
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• 2005

The NP-hard channel assignment problem becomes more and more important to use channels as efficiently as possible because there is a rapidly growing demand and the number of usable channel is very limited. The hybrid genetic and local search (HGLS) method in this paper is a hybrid method of genetic algorithm with no interference channel assignment (NICA) in clustering stage for diversified search and local search in tuning stage when the step of search is near convergence for minimizing blocking calls. The new representation of solution is also proposed for effective search and computation for channel assignment.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.3
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• pp.163-171
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• 2006

This paper considers a scheduling problem to minimize the sum of the associated scheduling (production/delivery times) cost and the delivery cost for an integrated system of a single production machine and various transportation vehicles with transportation mode selection allowed. Each transportation mode is provided with a fixed number of vehicles at the associated delivery time and cost. The proposed problem is characterized as being NP-hard. Some solution properties are also characterized. Therewith, three heuristic algorithms (called SPT-based, LWF-based and WSPT-based heuristic) and a branch-and-bound algorithm are derived. In order to evaluate the effectiveness and efficiency of the proposed algorithms, computational experiments are made with some numerical instances.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.1
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• pp.10-19
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• 2005

The minimum spanning tree (MST) problem is one of the traditional optimization problems. Unlike the MST, the degree constrained minimum spanning tree (DCMST) of a graph cannot, in general, be found using a polynomial time algorithm. So, finding the DCMST of a graph is a well-known NP-hard problem of importance in communications network design, road network design and other network-related problems. So, it seems to be natural to use evolutionary algorithms for solving DCMST. Especially, when applying an evolutionary algorithm to spanning tree problems, a representation and search operators should be considered simultaneously. This paper introduces a new tree representation scheme and a genetic operator for solving combinatorial tree problem using evolutionary algorithms. We performed empirical comparisons with other tree representations on several test instances and could confirm that the proposed method is superior to other tree representations. Even it is superior to edge set representation which is known as the best algorithm.

• IE interfaces
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• v.24 no.4
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• pp.341-350
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• 2011

This paper considers a problem of locating both distribution centers and retailers in a zone-dependent two-level distribution network where either a distribution center or a retailer should be located in each zone. Customer demands of each zone should be satisfied directly from either its own distribution center or its own retailer being supplied from a distribution center of another zone. The objective of the proposed problem is to minimize total cost being composed of distribution center/retailer setup costs and transportation costs. In the analysis, the problem is proved to be NP-hard, so that a branch-and-bound algorithm is derived for the problem. Numerical experiments show that the proposed branch-and-bound algorithm provides the optimal solution efficiently for some small problems.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06b
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• pp.470-473
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• 2011

본 논문에서는 첫째, 기존 HW/SW partitioning문제의 접근 방식 모델에서 다루지 못하였던 시간 의존적인 개발 기간, 판매 가격, 판매량, time-to-market 등의 요소들을 반영하는 multi-objective 최적화문제 형태의 새로운 "Sequential HW/SW Partitioning Optimization Framework(SPOF)"를 제시하고 둘째, 그 모델로 형식화된 NP-hard 문제를 일반적으로 해결하기위한 해법으로 SPOF의 형태에 맞게끔 변형한 chromosome과 genetic operation을 사용하는 메타휴리스틱 "Fast and Elitist Multi-objective Genetic Algorithm(NSGA-II)"을 제시한다. 실험을 통하여 NSGA-II의 최적 솔루션에의 수렴성을 보인다.