• 제목/요약/키워드: The First Assignment of Minimum cost

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Assignment Problem Algorithm Based on the First Selection Method of the Minimum Cost (최소비용 우선선택 방법에 기반한 할당 문제 알고리즘)

  • Lee, Sang-Un
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • 제13권5호
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    • pp.163-171
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    • 2013
  • This paper proposes an algorithm that seeks the optimal solution for an assignment problem through a simplified process. Generally it is Hungarian algorithm that is prevalently used to solve a given assignment problem. The proposed algorithm reduces 4 steps Hungarian algorithm into 2 steps. Firstly, the algorithm selects the minimum cost from a matrix and deletes the rest of the rows and columns. Secondly, it improves on the solution through reassignment process. For 27 balanced assignment problems and 7 unbalanced problems, the proposed algorithm has successfully yielded the optimal solution, which Genetic algorithm has failed. This algorithm is thus found to be an appropriate replacement of Hungarian algorithm.

Assignment-Change Optimization for the Problem of Bid Evaluation (입찰 평가 문제의 배정-변경 최적화)

  • Lee, Sang-Un
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • 제21권4호
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    • pp.171-176
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    • 2021
  • This paper deals with bid evaluation problem that chooses the vendors and quantity with minimum purchasing cost for bid information of setup cost and unit price. For this problem, the branch-and-bound(BB) and branch-and-cut(BC) methods are well-known. But these methods can be fail to obtain the optimal solution. This paper gets the initial feasible solution with procuring quantity assignment principle in accordance with the unit price or setup cost rank-first. Then procuring quantity moving optimization(vendor change) is execute take account of unit price or setup cost rank. As a result of experimentation, the propose algorithm is significantly lower compared to BB and BC.

Test Sequence Generation Using Multiple Unique State Signature(MUSS)

  • Jung, Yoon-Hee;Hong, Beom-Kee
    • Journal of Electrical Engineering and information Science
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    • 제2권6호
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    • pp.43-47
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    • 1997
  • A procedure presented in this paper generates test sequences to check the conformity of an implementation with a protocol specification, which is modeled as a deterministic finite state machine (FSM). Given a FSM, a common procedure of test sequence generation, first, constructs a directed graph which edges include the state check after each transition, and produces a symmetric graph G* from and, finally, finds a Euler tour of G*. We propose a technique to determine a minimum-cost tour of the transition graph of the FSM. The proposed technique using Multiple Unique State Signature (MUSS) solves an open issue that one MUIO sequence assignment may lead to two more edges of unit cost being replicated to from G* while an optimal assignment may lead to the replication of a single edge of high cost. In this paper, randomly generated FSMs have been studied as test cases. The result shows that the proposed technique saves the cost 4∼28% and 2∼21% over the previous approach using MUIO and MUSP, respectively.

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An Efficient Algorithm for Partial Scan Designs (효율적인 Partial Scan 설계 알고리듬)

  • Kim, Yun-Hong;Shin, Jae-Heung
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • 제53권4호
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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.

Hierarchical Cellular Network Design with Channel Allocation Using Genetic Algorithm (유전자 알고리즘을 이용한 다중계층 채널할당 셀룰러 네트워크 설계)

  • Lee, Sang-Heon;Park, Hyun-Soo
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 한국경영과학회 2005년도 추계학술대회 및 정기총회
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    • pp.321-333
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    • 2005
  • With the limited frequency spectrum and an increasing demand for cellular communication services, the problem of channel assignment becomes increasingly important. However, finding a conflict free channel assignment with the minimum channel span is NP hard. As demand for services has expanded in the cellular segment, sever innovations have been made in order to increase the utilization of bandwidth. The innovations are cellular concept, dynamic channel assignment and hierarchical network design. Hierarchical network design holds the public eye because of increasing demand and quality of service to mobile users. We consider the frequency assignment problem and the base station placement simultaneously. Our model takes the candidate locations emanating from this process and the cost of assigning a frequency, operating and maintaining equipment as an input. In addition, we know the avenue and demand as an assumption. We propose the network about the profit maximization. This study can apply to GSM(Global System for Mobile Communication) which has 70% portion in the world. Hierarchical network design using GA(Genetic Algorithm) is the first three-tier (Macro, Micro, Pico) model, We increase the reality through applying to EMC (Electromagnetic Compatibility Constraints). Computational experiments on 72 problem instances which have 15${\sim}$40 candidate locations demonstrate the computational viability of our procedure. The result of experiments increases the reality and covers more than 90% of the demand.

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Hierarchical Cellular Network Design with Channel Allocation (채널할당을 고려한 다중계층 셀룰러 네트워크 설계)

  • Park, Hyun-Soo;Lee, Sang-Heon
    • Journal of the military operations research society of Korea
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    • 제34권2호
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    • pp.63-77
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    • 2008
  • With the limited frequency spectrum and an increasing demand for cellular communication services, the problem of channel assignment becomes increasingly important. However, finding a conflict free channel assignment with the minimum channel span is NP hard. The innovations are cellular concept, dynamic channel assignment and hierarchical network design. We consider the frequency assignment problem and the base station placement simultaneously. Our model takes the candidate locations emanating from this process and the cost of assigning a frequency, operating and maintaining equipment as an input. Hierarchical network design using genetic algorithm is the first three-tier (Macro, Micro, Pico) model. We increase the reality through applying to Electromagnetic Compatibility Constraints. Computational experiments on 72 problem instances which have $15{\sim}40$ candidate locations demonstrate the computational viability of our procedure. The result of experiments increases the reality and covers 90% of the demand.

Optimal Algorithm for Transshipment Problem (중개수송 문제 최적 알고리즘)

  • Lee, Sang-Un;Choi, Myeong-Bok
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • 제13권1호
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    • pp.153-162
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    • 2013
  • This paper proposes the most simple method for optimal solution of the transshipment problem. Usually the transshipment problem is solved by direct linear programming or TSM (Transportation Simplex Method). The method using TSM has two steps. First it is to get a initial solution using NCM, LCM, or VAM, second to refine the initial solution using MOD or SSM. However the steps is complex and difficult. The proposed method applies the method that transforms transshipment problem to transportation problem. In the proposed method it simply selects the minimum cost of rows about transportation problem, and then it applies the method that assigns a transported volume as an ascending sort of the costs of rows about the selected costs. Our method makes to be very fast got the initial value. Also we uses the method that controls assignment volume, if a heavy item of cost is assigned to a transported volume and it has a condition to be able to transform to more lower cost. The proposed algorithm simply got the optimal solution with applying to 11 transshipment problem.

Aggregate Planning Using Least Cost First Assignment Algorithm of Transportation Problem (운송 문제의 최소비용 우선 배정 알고리즘을 적용한 총괄계획)

  • Lee, Sang-Un
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • 제21권5호
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    • pp.181-188
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    • 2021
  • In preparing a aggregate production plan(APP), the transportation method generally uses a linear planning(LP) software package for TSM(transportation simplex method), which seeks initial solutions with either NCM, LCM, or VAM specialized in transportation issues and optimizes them with either SSM or MODI. On the other hand, this paper proposes a transportation method that easily, quickly, and accurately prepares a APP without software package assistance. This algorithm proposed simply assigned to least cost-first, and minimized the inventory periods. Applying the proposed algorithm to 6-benchmarking data, this algorithm can be obtained better optimal solution than VAM or LP for 4 data, and we obtain the same results for the remained 2 data.

Simple Solution for Multi-commodity Transportation Problem (복합상품 운송 문제의 간단한 해법)

  • Lee, Sang-Un;Choi, Myeong-Bok
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • 제13권5호
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    • pp.173-181
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    • 2013
  • This paper proposes a heuristic optimal solution of multicommodity transportation problem. The proposed algorithm has 3 steps. First the proposed algorithm transforms multicommodity transshipment problem to a general transportation problem, but if the problem is a multicommodity transportation problem, it is not transformed. And the multicommodity is disassembled to a single commodity. Second if it is a multicommodity transportation problem, the algorithm selects the minimum cost according to commodity, on the other hand if it is a multicommodity transshipment problem, the algorithm directly selects the minimum cost based on demand area. And the algorithm assigns carloadings to be satisfied the supply and demand quantity. The algorithm repeats these processes until a given demand quantity is satisfied. Last if it has a condition that is able to reduce the transportation expense, the proposed algorithm controls the assignment quantity of the initial value that got from the step 2. The proposed algorithm was applied to two multicommodity transportation problem and three multicommodity transshipment problem and it got more good result than an existing linear programming method.