• Industrial Engineering and Management Systems
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• 제15권1호
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• pp.1-10
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• 2016

This paper presents a fast sequencing algorithm for a mixed model assembly line with multiple workstations which minimize the total utility work and idle time. We compare the proposed algorithms with another heuristic, the Tsai-based heuristic, for a sequencing problem that minimizes the total utility works. Numerical experiments are used to evaluate the performance and effectiveness of the proposed algorithm. The Tsai-based heuristic performs best in terms of utility work, but the fast sequencing algorithm performs well for both utility work and idle time. However, the computational complexity of the fast sequencing algorithm is O (KN) while the Tsai-based algorithm is O (KNlogN). Actual computational time of the fast sequencing heuristic is 2-6 times faster than that of the Tsai-based heuristic.

• 한국정보시스템학회지:정보시스템연구
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• 제28권4호
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• pp.175-197
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• 2019

Purpose This study develops a heuristic algorithm to solve the time-resource tradeoffs in project scheduling problems with a real basis. Design/methodology/approach Resource constrained project scheduling problem with time-resource tradeoff is well-known as one of the NP-hard problems. Previous researchers have proposed heuristic that minimize Makespan of project scheduling by deriving optimal combinations from finite combinations of time and resource. We studied to solve project scheduling problems by deriving optimal values from infinite combinations. Findings We developed heuristic algorithm named Push Algorithm that derives optimal combinations from infinite combinations of time and resources. Developed heuristic algorithm based on simulated annealing shows better improved results than genetic algorithm and further research suggestion was discussed as a project scheduling problem with multiple resources of real numbers.

• 전자공학회논문지B
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• 제32B권1호
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• pp.11-20
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• 1995

A new graph problem is formulated to limit the maximum path length of a general directed graph when a minimal set of vertices together with their incident edges are removed from the graph. An optimal algorithm and a heuristic algorithm are proposed and the proposed heuristic algorithm is shown to be effective through experiments using a collection of graphs obtained from large sequential circuits. The heuristic algorithm is based on a feedback vertex set algorithm based on graph reduction.

• 한국게임학회 논문지
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• 제17권5호
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• pp.123-132
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• 2017

경로 탐색 알고리즘은 이동 가능한 에이전트가 게임 내의 가상 월드에서 현재 위치로부터 목적지까지 가는 경로를 탐색하는 알고리즘을 뜻한다. 기존의 경로 탐색 알고리즘은 A*, Dijkstra와 같이 비용기반으로 그래프 탐색을 수행한다. A*와 Dijkstra는 월드 맵에서 이동 가능한 노드와 에지 정보들을 필요로 해서 맵의 정보가 다양하고 많은 온라인 게임에 적용하기 힘들다. 본 논문에서는 가변환경이나 맵의 데이터가 방대한 게임에서 적용 가능한 경로 탐색 알고리즘을 개발하기 위해 맵의 정보 없이 교배, 교차, 돌연변이, 진화 연산을 통해 해를 찾는 유전 알고리즘(Genetic Algorithm, GA)을 활용한 Heuristic-based Genetic Algorithm Path-finding(HGAP)를 제안한다. 제안하는 알고리즘은 Binary-Coded Genetic Algorithm을 기반으로 하며 목적지에 더 빨리 도달하기 위해 목적지로 가는 경로를 추정하는 휴리스틱 연산을 수행하여 경로를 탐색한다.

• 한국공간정보시스템학회 논문지
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• 제10권2호
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• pp.35-48
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• 2008

이 논문에서는 단말기 기반 시스템에서 경로를 탐색할 때 탐색비용을 줄이고, 경로탐색의 질을 높이기 위해 동적 휴리스틱을 제안한다. 동적 휴리스틱이란 고정된 정보가 아닌 서버로부터 지속적으로 전송받는 휴리스틱으로, 교통정보를 계산한 데이터이다. 서버 기반의 경로탐색 서비스는 서버에서 경로를 탐색하여 결과를 클라이언트에 제공하지만, 제안하는 방법은 휴리스틱 정보만을 클라이언트에 전송하고 이를 활용하여 경로탐색을 하게 된다. 이 논문에서는 제안하는 동적 휴리스틱을 적용하기 위해 새로운 알고리즘을 제안한다. 제안하는 동적 휴리스틱은 지도를 그리드로 나누고, 각 그리드는 구역내 간선들의 최저속도 정보를 가진다. 그리드의 최저속도가 기준치에 미달되면 해당 그리드를 제거하고 경로를 탐색한다.

• 융합신호처리학회논문지
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• 제3권2호
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• pp.89-95
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• 2002

글로벌 라우팅(global routing)은 VLSI 설계 과정중의 하나로, 네트리스트의 모든 네트들을 연결하기 위하여 각 네트들을 라우팅 영역(routing area)에 할당시키는 문제이며, 글로벌 라우팅에서 최적의 해를 얻기 위해 maze routing 알고리즘, line-probe 알고리즘, shortest path 기반 알고리즘, Steiner tree 기반 알고리즘등이 이용된다. 본 논문에서는 라우팅 그래프에서 최단 경로 Steiner tree 탐색방법인 weighted network heuristic(WNH)과 이를 기반으로 하는 글로벌 라우팅 유전자 알고리즘(genetic algorithm; GA)을 제안하였으며, 제안한 방식을 시뮬레이티드 어닐링(SA) 방식과 비교, 분석하였다.

• 대한산업공학회지
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• 제42권3호
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• pp.173-181
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• 2016

This paper deals with the single-hoist and multiple-products scheduling problem. Although a mixed integer linear programming model for the problem was developed earlier, a branch-and-bound based heuristic algorithm is proposed in this paper to solve the big-size problems in real situation. The algorithm is capable of handling problems incorporating different product types, jobs in the process, and tank capacities. Using a small example problem the procedure of the heuristic algorithm is explained. To assess the performance of the heuristic we generate a bigger example problem and compare the results of the algorithm proposed in this paper with the optimal solutions derived from the mathematical model of earlier research. The comparison shows that the heuristic has very good performance and the computation time is sufficiently short to use the algorithm in real situation.

• Structural Engineering and Mechanics
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• 제52권2호
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• pp.405-426
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• 2014

In this paper, a new meta-heuristic algorithm named Ranked Particles Optimization (RPO), is presented. This algorithm is not inspired from natural or physical phenomena. However, it is based on numerous researches in the field of meta-heuristic optimization algorithms. In this algorithm, like other meta-heuristic algorithms, optimization process starts with by producing a population of random solutions, Particles, located in the feasible search space. In the next step, cost functions corresponding to all random particles are evaluated and some of those having minimum cost functions are stored. These particles are ranked and their weighted average is calculated and named Ranked Center. New solutions are produced by moving each particle along its previous motion, the ranked center, and the best particle found thus far. The robustness of this algorithm is verified by solving some mathematical and structural optimization problems. Simplicity of implementation and reaching to desired solution are two main characteristics of this algorithm.

• ETRI Journal
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• 제44권4호
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• pp.560-572
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• 2022

H²RDC (heuristic handover based on RCC-DTSK-C), a heuristic algorithm based on a highly interpretable deep Takagi-Sugeno-Kang fuzzy classifier, is proposed for suppressing the mobile heterogeneous networks problem of frequent handover and handover ping-pong in the multibase-station scenario. This classifier uses a stack structure between subsystems to form a deep classifier before generating a base station (BS) priority sequence during the handover process, and adaptive handover hysteresis is calculated. Simulation results show that H²RDC allows user equipment to switch to the best antenna at the optimal time. In high-BS density load and mobility scenarios, the proposed algorithm's handover success rate is similar to those of classic algorithms such as best connection (BC), self tuning handover algorithm (STHA), and heuristic for handover based on AHP-TOPSIS-FUZZY (H²ATF). Moreover, the handover rate is 83% lower under H²RDC than under BC, whereas the handover ping-pong rate is 76% lower.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 2001년도 The Seoul International Simulation Conference
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• pp.263-268
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• 2001

In this paper, we present a new heuristic algorithm fur buffer allocation in FMS (Flexible Manufacturing System). It is conducted by using a genetic algorithm and simulation. First, we model the system by using a simulation software, \"Arena\". Then, we apply a genetic algorithm to achieve an optimal solution. VBA blocks, which are kinds of add-in functions in Arena, are used to connect Arena with the genetic algorithm. The system being modeled has seven workstations, one loading/unloading station, and three AGVs (Automated Guided Vehicle). Also it contains three products, which each have their own machining order and processing times. We experimented with two kinds of buffer allocation problems with a proposed heuristic algorithm, and we will suggest a simple heuristic approach based on processing times and workloads to validate our proposed algorithm. The first experiment is to find a buffer profile to achieve the maximum throughput using a finite number of buffers. The second experiment is to find the minimum number of buffers to achieve the desired throughput. End of this paper, we compare the result of a proposed algorithm with the result of a simple buffer allocation heuristic based on processing times and workloads. We show that the proposed algorithm increase the throughput by 7.2%.t by 7.2%.