• 대한산업공학회지
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• 제21권3호
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• pp.329-343
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• 1995

Traditionally, machining process sequence was influenced and constrained by the design information obtained from CAD data base, i.e., class of operations, geometric shape, tooling, geometric tolerance, etc. However, even though all the constraints from design information are considered, there may exist more than one way to feasibly machine parts. This research is focused on the integrated problem of operations sequencing and machine tools selection in the presence of the product mix and their production volumes. With the transitional costs among machining operations, the operation sequencing problem can be formulated as a well-known Traveling Salesman Problem (TSP). The transitional cost between two operations is expressed as the sum of total machining time of the parts on a machine for the first operation and transportation time of the parts from the first machine to a machine for the second operation. Therefore, the operation sequencing problem formulated as TSP cannot be solved without transitional costs for all operation pairs. When solved separately or serially, their mutual optima cannot be guaranteed. Machining operations sequencing and machine tool selection problems are two core problems in process planning for discretely machined parts. In this paper, the interrelated two problems are integrated and analyzed, zero-one integer programming model for the integrated problem is formulated, and the solution methods are developed using a Tabu Search technique.

• 산업공학
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• 제25권3호
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• pp.365-375
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• 2012

An Unmanned Aerial Vehicle (UAV) is a powered pilotless aircraft, which is controlled remotely or autonomously. UAVs are an attractive alternative for many scientific and military organizations. UAVs can perform operations that are considered to be risky or uninhabitable for humans. UAVs are currently employed in many military missions and a number of civilian applications. For accomplishing the UAV's missions, guarantee of survivability should be preceded. The main objective of this study is to suggest a mathematical programming model and a $A^*PS$_PGA (A-star with Post Smoothing_Parallel Genetic Algorithm) for Multiple UAVs's path planning to maximize survivability. A mathematical programming model is composed by using MRPP (Most Reliable Path Problem) and MTSP (Multiple Traveling Salesman Problem). After transforming MRPP into Shortest Path Problem (SPP),$A^*PS$_PGA applies a path planning for multiple UAVs.

• 정보처리학회논문지B
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• 제8B권6호
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• pp.601-608
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• 2001

The automated assignment of multiple tasks to executing agents is a key problem in the area of multi-agent systems. In many domains, significant savings can be achieved by reallocating tasks among agents with different costs for handling tasks. The automation of task reallocation among self-interested agents requires that the individual agents use a common negotiation protocol that prescribes how they have to interact in order to come to an agreement on "who does what". In this paper, we introduce the multi-agent Traveling Salesman Problem(TSP) as an example of task reallocation problem, and suggest the Vickery auction as an interagent negotiation protocol for solving this problem. In general, auction-based protocols show several advantageous features: they are easily implementable, they enforce an efficient assignment process, and they guarantce an agreement even in scenarios in which the agents possess only very little domain-specific Knowledge. Furthermore Vickrey auctions have the additional advantage that each interested agent bids only once and that the dominant strategy is to bid one′s true valuation. In order to apply this market-based protocol into task reallocation among self-interested agents, we define the profit of each agent, the goal of negotiation, tasks to be traded out through auctions, the bidding strategy, and the sequence of auctions. Through several experiments with sample multi-agent TSPs, we show that the task allocation can improve monotonically at each step and then finally an optimal task allocation can be found with this protocol.

• 한국정보과학회논문지:소프트웨어및응용
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• 제28권7호
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• pp.467-477
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• 2001

반응적 타부 탐색은 단순한 타부 탐색과 비교해서 중장기 메모리를 이용한 학습을 통하여 타부리스트의 크기를 반응적으로 변화시킴으로써 NP-hard 문제에 속하는 다양한 조합 최적해 문제에 대해서 좋은 해를 효율적으로 찾는다. 본 논문에서는 반응적 타부 탐색에 있어서 중장기 메모리를 이용한 탈출 메커니즘으로 이웃 해 전략 전환 메커니즘이라는 개념을 제시한다. 제시된 이웃 해 전략 전환 메커니즘을 이용한 반응적 타부 탐색을 특정 공과 대학의 강의 시간표 작성 문제와 외판원문제 (traveling salesman problem)에 적용하여 기존의 반응적 타부 탐색과 비교 분석을 하였다. 전산 실험 결과 제시된 알고리즘은 기존의 반응적 타부 탐색 알고리즘에 비교하여 더 좋은 해를 더 짧은 시간에 찾아주었다.

• 한국정밀공학회지
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• 제16권12호
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• pp.109-118
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• 1999

The objective of this research is to develop an effective inspection planning strategy for sculpture surfaces in OMM(On-Machine Measurement) process. As a first step, effective measuring point locations are determined to obtain optimum results for given sampling numbers. Two measuring point selection methods are suggested in this study based on newly proposed CAD/CAM/CAI integration concept: (1) by the prediction of cutting errors, (2) by considering cutter contact points to avoid the measurement errors caused by cusps. As a next step, the TSP(Traveling Salesman Problem)algorithm is applied to minimize the probe moving distance. Appropriate simulations and experiments are performed to verify the proposed inspection planning strategy in this study, and the results are analyzed.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2011년도 한국컴퓨터종합학술대회논문집 Vol.38 No.1(B)
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• pp.21-24
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• 2011

본 논문은 확장성(scalability)과 견고함(robustness)을 강조하는 새로운 형태의 병렬 분산 메타-휴리스틱 프레임워크를 제안하고 있다. PADO (Parallel And Distributed Optimization framework) 라고 이름 지어진 본 프레임워크는 이종의 계산 및 통신 자원들을 활용하여 메타-휴리스틱 알고리즘을 병렬화하고 스케일러블한 속도 향상을 얻을 수 있다. 본 프레임워크는 기존의 시퀀셜(sequential) 최적화 프레임워크에 메타-휴리스틱 알고리즘의 병렬화 기법중 하나인 island 모델을 개선하여 구현하였다. 본 연구는 부분적으로 정렬된 지식 공유 방법(Partially Ordered Knowledge Sharing) 모델을 이용하여 병렬 환경 코디네이션(coordination) 오버헤드를 줄였고 계산 노드에 대한 확장성을 얻었다. 본 프레임워크를 통해 기존의 많은 메타-휴리스틱 알고리즘들을 재사용 할 수 있고 다양한 분야의 최적화 문제에 적용 할 수 있으며 계산량이 많은 메타-휴리스틱 알고리즘을 병렬화를 통해 문제를 푸는 시간을 단축 할 수 있다. 순회 판매원 문제(Traveling Salesman Problem)를 통해 프레임워크의 실효성을 검증하였다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2001년도 추계학술발표논문집 (하)
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• pp.1151-1154
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• 2001

외판원 문제(Traveling Salesman Problem)는 주어진 n개의 도시들과 그 도시들간의 거리비용이 주어졌을 때, 모든 도시들을 정확히 한번씩만 방문하면서 걸린 비용이 최소가 드는 경로를 찾는 문제로 최적해(optimal)을 구하는 것은 전형적인 NP-완전 문제중의 하나이다. 따라서 외판원 문제를 해결하는 다양한 알고리즘들이 개발되고 있다. 특히 요즈음은 실제 생체 분자(bio-molecule)를 계산의 도구로 사용하는 새로운 계산 방법인 DNA 컴퓨팅은 DNA 분자가 잠재적으로 가지고 있는 막대한 병렬성을 이용해서 NP-완전 문제들을 해결하고자 하는 연구들이 땀이 진행되고 있다. 그러나 아직 실제 생체 분자의 특성을 잘 반영하는 계산 모델이나 분자 생물학에서 사용하는 연산들이 많이 개발되지 알아 계산 효율이 비교적 좋지 않다. 따라서 본 논문에서는 외판원 문제를 해결하기 위한 DAN컴퓨팅의 새로운 중합 효소 연쇄 반응(Polymerase Chain Reaction, PCR) 연산을 개발하였다.

• 경영과학
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• 제17권2호
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• pp.87-95
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• 2000

This paper presents two analytical approaches to determine the vehicle fleet size for container shuttle service. The shuttle service can be defined as the repetitive travel between the designated places during working period. In the first approach, the transportation model is adopted in order to determine the number of vehicles required. Its advantages and disadvantages in practical application are also discussed. In the second approach, a logical network which is oriented on job is transformed from a physical network which is focused on demand site. Nodes on the logical network represent jobs which include loaded travel, loading and unloading and arcs represent empty travel for the next jobs which include loaded travel, loading and unloading and arcs represent empty travel for the next job. Then a mathematical formulation is constructed similar to the multiple traveling salesman problem (TSP). A solution procedure is carried out based on the well-known insertion heuristic with the real world data.

• Management Science and Financial Engineering
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• 제7권2호
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• pp.1-11
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• 2001

Gouveia and Pires (European Journal of Operations Research 112(1999) 134-146) have proposed four extended formulations having precedence variables as extra variables and characterized the projections of three of the four formulations into the natural variable space. In Gouveia and Pires (Discrete Applied Mathematics 112 (2001)), they also have introduced some other extended formulations with the same extra variables and conjectured that the projection of one of the proposed formulations is equivalent to the one proposed by Dantzig, Fulkerson, and Johnson (Operations Research 2(1954) 393-410). In this paper, we provide a unifying framework based on which we give alternative proofs on the projections of three extended formulations and new proofs on those of two formulations appeared in Gouveia and Pires(1999, 2001).

• 산업공학
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• 제10권1호
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• pp.223-235
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• 1997

The process of determining the optimal tool path in PCB(printed circuit board) drilling operations is identical with that of solving a TSP(traveling salesman problem). However, the optimal solution will be ruined when a drill bit needs tracking back in its tool paths. The back tracking occurrences shorten a life of the main spindle and result in inaccurate mechanical movements. In this study, the performances of four heuristics(Nearest Neighbor, Convex Hull, Greatest Angle and Most Eccentric Ellipse) are evaluated to obtain feasible tool paths along with less number of back trackings for a large number of holes(more than 2000holes/bit) and to generate corresponding NC codes for a given CNC drill. Also, the operations of these algorithms are visualized to show a user the graphic image of tool visitation with PCB holes on a computer screen.