• Journal of Advanced Marine Engineering and Technology
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• v.35 no.3
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• pp.341-347
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• 2011

The redundancy allocation problem (RAP) is a famous NP.complete problem that has beenstudied in the system reliability area of ships and airplanes. Recently meta-heuristic techniques have been applied in this topic, for example, genetic algorithms, simulated annealing and tabu search. In particular, tabu search (TS) has emerged as an efficient algorithmic approach for the series-parallel RAP. However, the quality of solutions found by TS depends on the initial solution. As a robust and efficient methodology for the series-parallel RAP, the hybrid metaheuristic (TSA) that is a interactive procedure between the TS and SA (simulated annealing) is developed in this paper. In the proposed algorithm, SA is used to find the diversified promising solutions so that TS can re-intensify search for the solutions obtained by the SA. We test the proposed TSA by the existing problems and compare it with the SA and TS algorithm. Computational results show that the TSA algorithm finds the global optimal solutions for all cases and outperforms the existing TS and SA in cases of 42 and 56 subsystems.

• Proceedings of the KIEE Conference
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• summer
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• pp.36-38
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• 2004

This paper presents an application of parallel hybrid Genetic Algorithm-Tabu Search (GA-TS) algorithm to search an optimal solution of a recokiguration in distribution system. In parallel hybrid CA-TS, after CA operations, stings which are not emerged in the past population are selected in the reproduction procedure. After reproduction operation, if there are many strings which are in the past population, we add new random strings into the population, if there's no improvement for the predetermined iteration, local search procedure is executed by TS for the strings with high fitness function value. To show the usefulness of the proposed method, developed algorithm has been tested and compared on a distribution system in the reference paper.

• Proceedings of the KIEE Conference
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• summer
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• pp.446-448
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• 2004

This paper presents an application of parallel hybrid Genetic Algorithm-Tabu Search (GA-TS) algorithm to search an optimal solution of a service restoration in distribution system. In parallel hybrid GA-TS, after GA operations, strings which are not emerged in the past population are selected in the reproduction procedure. After reproduction operation, if there are many strings which are in the past population, we add new random strings into the population. If there's no improvement for the predetermined iteration, local search procedure is executed by f for the strings with high fitness function value. To show the usefulness of the proposed method, developed algorithm has been tested and compared on a practical distribution system in Korea.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.843-859
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• 2024

The university course scheduling problem (UCSP) aims at optimally arranging courses to corresponding rooms, faculties, students, and timeslots with constraints. Previously, the university staff solved this thorny problem by hand, which is very time-consuming and makes it easy to fall into chaos. Even some meta-heuristic algorithms are proposed to solve UCSP automatically, while most only utilize one single algorithm, so the scheduling results still need improvement. Besides, they lack an in-depth analysis of the inner algorithms. Therefore, this paper presents a novel and practical approach based on Tabu search and simulated annealing algorithms for solving USCP. Firstly, the initial solution of the UCSP instance is generated by one construction heuristic algorithm, the first fit algorithm. Secondly, we defined one union move selector to control the moves and provide diverse solutions from initial solutions, consisting of two changing move selectors. Thirdly, Tabu search and simulated annealing (SA) are combined to filter out unacceptable moves in a parallel mode. Then, the acceptable moves are selected by one adaptive decision algorithm, which is used as the next step to construct the final solving path. Benefits from the excellent design of the union move selector, parallel tabu search and SA, and adaptive decision algorithm, the proposed method could effectively solve UCSP since it fully uses Tabu and SA. We designed and tested the proposed algorithm in one real-world (PKNU-UCSP) and ten random UCSP instances. The experimental results confirmed its effectiveness. Besides, the in-depth analysis confirmed each component's effectiveness for solving UCSP.

• Structural Engineering and Mechanics
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• v.23 no.4
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• pp.325-337
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• 2006

A hybrid structural design and optimization methodology that combines the strengths of genetic algorithms, local search techniques, and parallel computing is developed to evolve optimal truss systems in this research effort. The primary objective that is met in evolving near-optimal or optimal structural systems using this approach is the capability of satisfying user-defined design criteria while minimizing the computational time required. The application of genetic algorithms to the design and optimization of truss systems supports conceptual design by facilitating the exploration of new design alternatives. In addition, final shape optimization of the evolved designs is supported through the refinement of member sizes using local search techniques for further improvement. The use of the hybrid approach, therefore, enhances the overall process of structural design. Parallel computing is implemented to reduce the total computation time required to obtain near-optimal designs. The support of human-computer interaction during layout optimization and local optimization is also discussed since it assists in evolving optimal truss systems that better satisfy a user's design requirements and design preferences.

• Journal of the military operations research society of Korea
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• v.9 no.1
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• pp.51-61
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• 1983

Lagrangian relaxation is used to the problem of scheduling jobs on unrelated parallel processors with the objective of minimizing makespan. The implicit condition for optimality is drawn out explicitly in order to apply the subgradient algorithm. To obtain the optimal solution, branch-and-bound-search method is devised. In the search, the special structure of the problem is exploited effectively, Some computational experiences with the algorithm are presented, and comparisons are made with the Land and Doig method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.60
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• pp.67-72
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• 2000

In this paper we consider to parallel machines scheduling problems for minimizing mean tardiness that is known NP-complete. This problems is classified into two cases, one of which is the case which processing time are identical and the other, nonidentical. A Tabu Search method is applied to the problems considered in this paper to get an improved solution. To this end, we design move attribute, Tabu attribute and Tabu tenure, and thereafter perform the experiments to the problems.

• Journal of the Korean Statistical Society
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• v.17 no.2
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• pp.134-145
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• 1988

The basic conditions for a parallel-flats fraction to be a search design of Resolution III.2 have been developed in Um (1980, 1981, 1983, 1984). In this paper, a series of resolution III.2 search designs for $3^n, n=4, 5, 6$, are presented.

• Journal of the Korean Statistical Society
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• v.9 no.2
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• pp.126-134
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• 1980

In this paper, Srivastava's Theorem for the search design is considered, with additional assumptions, to the $3^n$ parallel flats fractions. It is also expressed in terms of ACPM.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.2 s.344
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• pp.51-59
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• 2006

Von Neumann architecture suffers from the interface between the central processing unit and the memory, which is called 'Von Neumann bottleneck' In this paper, we propose a scalable general-purpose associative processor (AP) based on content-addressable memory (CAM) which solves this problem and is suitable for the search-oriented applications. We propose an efficient instruction set and a structural scalability to extend for larger applications. We define twelve instructions and provide some reduced instructions to speed up which execute two instructions in a single instruction cycle. The proposed AP performs in a bit-serial, word-parallel fashion and can be considered as a 32-bit general-purpose parallel processor with a massively parallel SIMD structure. We design and simulate a maximum/minumum search greater-than/less-than search, and parallel addition to verify the proposed architecture. The algorithms are executed in a constant time O(k) regardless of the number of input data.