• Journal of the Korea Society of Computer and Information
• /
• v.19 no.11
• /
• pp.175-181
• /
• 2014

This paper suggests O(m) polynomial time heuristic algorithm to obtain the solution for the driver scheduling problem, DSP, that has been classified as NP-complete problem. The proposed algorithm gets the initial assignment of n minimum number of drivers from given m schedules. Nextly, this algorithm gets the minimum total time (TC) using 5 rules of swap and insert for decrease of over times (OT) and idle times (IT). Although this algorithm is a heuristic polynomial time algorithm with O(m) time complexity rules to be find a optimal (or approximate) solution, this algorithm is equal to metaheuristic methods for the 5 experimental data. To conclude, this paper shows the DSP is not NP-complete problem but Polynomial time (P)-problem with polynomial time rules.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2000.04a
• /
• pp.147-150
• /
• 2000

본 논문은 단일설비로 다종제품을 생산하는 생산시스템에서 생산준비비용의 절감효과를 고려한 동적생산계획 모형을 다룬다. 이 모형에서 각 제품에 대한 수요는 유한계획기간에서 동적으로 발생하고 추후조달은 허용되지 않으며 투입자원은 한 종류가 사용된다. 또한, 생산기간마다 생산설비는 다종제품을 동시에 생산하고 이때 각 제품의 생산량은 전체 투입자원량의 일정비율로 생산된다. 이 모형에서 총비용은 생산준비 비용의 절감을 위한 투자비용, 생산준비비용, 각 제품별 재고유지비용으로 구성된다. 본 논문에서는 절감된 생산준비비용 하에서의 최적생산계획과 생산준비비용의 절감을 위한 최적투자액을 동시에 결정할 수 있는 휴리스틱 알고리즘를 제시한다. 또한, 선형 및 지수 감소함수 형태의 생산준비비용 절감함수 하에서 다양한 문제들을 대상으로 한 시뮬레이션 실험을 통해 제시한 휴리스틱 알고리즘의 효율성을 검증한다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2013.06a
• /
• pp.216-217
• /
• 2013

대형 조선소에서 하루 수십, 수백 개의 블록 이동이 있고 이동량이 많아지면 트랜스포터의 수, 운전기사, 신호수의 요구 증가를 야기해 비용 증가에 영향을 미친다. 또한 조선소에서 블록 이동은 공정 사이의 흐름에 영향을 미치며 전체 일정을 지연시킬 수도 있다. 그러므로 잘짜여진 블록 이동문제는 생산성 증가과 총 비용 감소에 있어 중요하다. 트랜스포터를 이용하여 블록을 이동하는데 트랜스포터란 고가의 특수운반차량으로 조선소에서 종류별(수백톤급)로 보유하고 있다. 트랜스포터는 가용 중량 이상의 블록을 이동할 수 없는데 이 때 두 대 이상의 차량을 결합하여 운반할 수 있다. 본 연구에서는 블록 무게와 트랜스포터의 적재 용량을 고려한 트랜스포터의 일정계획 문제를 다룬다. 계획된 공정 시간에 맞춰 블록이 도착할 수 있도록(지연시간 최소화)하는 모형을 정의하고 휴리스틱 알고리즘을 제안한다. 그리고 실험을 통해 최적화 모형과 휴리스틱 알고리즘의 효과를 검증하고자 한다.

• Journal of Korea Game Society
• /
• v.15 no.4
• /
• pp.179-188
• /
• 2015

The A* algorithm is a well-known pathfinding algorithm. However, if the information about obstacles is not exploited, the algorithm may collide with obstacles or lead into swamp areas unnecessarily. In this paper, we propose new heuristic functions using the information of obstacles to avoid them or swamp areas. It takes time to process the information of obstacles before starting pathfinding, but it may not cause any problems most of cases because it is not processed in real time. We showed that the proposed methods could reduce the search space effectively through experiments. Furthermore, we showed that heuristic functions using obstacle information could reduce the search space effectively without processing obstacle information at all.

• The KIPS Transactions:PartA
• /
• v.11A no.7 s.91
• /
• pp.499-510
• /
• 2004

This paper proposes a heuristic load balancing algorithm for multiprocessor systems. The algorithm minimizes the number of idle links to distribute load traffic and reduces its communication cost. Each processor iteratively tries to transfer unit load to/from every neighbor processors. However, real load transfer is collectively done after complete load traffic calculation to minimize useless traffic. The proposed algorithm can be employed in various interconnection topologies with slight modifications. In this paper, it is applied to both hypercube and mesh environments. For performance evaluation, simulation studies are performed. The performance of proposed algorithm is compared to those of two well-known algorithms. The results show that the proposed algorithm always balances the loads perfectly. Furthermore, it reduces the communication costs by $70{\%}{\~}90{\%}$ in the hypercube ; and it reduces the cost by $\75{\%}$ in the mesh, compared to existing algorithms.

• Journal of KIISE:Computer Systems and Theory
• /
• v.33 no.8
• /
• pp.486-494
• /
• 2006

In this paper, we introduce a new solution for the load balancing problem, an important issue in parallel processing. Our heuristic load balancing technique called MGA effectively combines the benefit of both mean-field annealing (MFA) and genetic algorithms (GA). We compare the proposed MGA algorithm with other mapping algorithms (MFA, GA-l, and GA-2). A multiprocessor mapping algorithm simulation has been developed to measure performance improvement ratio of these algorithms. Our experimental results show that our new technique, the composition of heuristic mapping methods improves performance over the conventional ones, in terms of solution quality with a longer run time.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.47 no.8
• /
• pp.74-84
• /
• 2010

In this paper, we propose a preference-based shortest path algorithm which is combined with Ant Colony Optimization (ACO) and A* heuristic algorithm. In recent years, with the development of ITS (Intelligent Transportation Systems), there has been a resurgence of interest in a shortest path search algorithm for use in car navigation systems. Most of the shortest path search algorithms such as Dijkstra and A* aim at finding the distance or time shortest paths. However, the shortest path is not always an optimum path for the drivers who prefer choosing a less short, but more reliable or flexible path. For this reason, we propose a preference-based shortest path search algorithm which uses the properties of the links of the map. The preferences of the links are specified by the user of the car navigation system. The proposed algorithm was implemented in C and experiments were performed upon the map that includes 64 nodes with 118 links. The experimental results show that the proposed algorithm is suitable to find preference-based shortest paths as well as distance shortest paths.

• Journal of the military operations research society of Korea
• /
• v.36 no.3
• /
• pp.29-42
• /
• 2010

In this study, the weapon-target assignment problem arising in military application of operations research is considered. We reformulated the problem in order to simplify the solution methods based on genetic algorithms and heuristics. Since the problem is well known as NP-complete and cannot be solved in polynomial time, such solution methods have been widely used to obtain good solutions. Two chromosome representations--target number representation and permutation representation--in genetic algorithm are compared. In addition, a construction heuristic and three improving heuristics are developed. Several experiments under the condition of transitivity rules in weapon's kill probability have been accomplished. It shows that the construction heuristic and exchange-based improving heuristic guarantees good solutions within a second and the performance of construction heuristic is sensitive to transitivity rules.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.22 no.1
• /
• pp.95-101
• /
• 2022

The two-sided assembly line balancing problem is a kind of NP-hard problem. This problem primarily can be solved metaheuristic method. This paper suggests parallel clustering algorithm that each left and right-sided workstation assigned by operations with T_i = c^* ± α < c, c^* = ${\lceil}$W/m^*${\rceil}$ such that M^* = ${\lceil}$W/c${\rceil}$ for precedence diagram of two-sided assembly line with total complete time W and cycle time c. This clustering performs forward direction from left to right or reverse direction from right to left. For the 4 experimental data with 17 cycle times, the proposed algorithm can be obtain the minimum number of workstations m^* and can be reduce the cycle time to T_max < c then metaheuristic methods. Also, proposed clustering algorithm maximizes the line efficiency and minimizes the variance between workers operation times.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.8
• /
• pp.67-75
• /
• 2013

The advantages of the orthogonal frequency division multiplexing (OFDM) are high spectral efficiency, resiliency to RF interference, and lower multi-path distortion. To further utilize vast channel capacity of the multiuser OFDM, one has to find the efficient adaptive subchannel and bit allocation among users. In this paper, we compare the performance of the linear programming dual of the 0-1 integer programming formulation with the existing convex optimization approach for the optimal subchannel and bit allocation problem of the multiuser OFDM. Utilizing tight lower bound provided by the LP dual formulation, we develop a primal heurisitc algorithm based on the LP dual solution. The performance of the primal heuristic is compared with MAO, ESA heuristic solutions, and integer programming solution on MATLAB simulation on a system employing M-ary quadrature amplitude modulation (MQAM) assuming a frequency-selective channel consisting of three independent Rayleigh multi-paths.