• 대한전기학회논문지:전력기술부문A
• /
• 제48권3호
• /
• pp.234-240
• /
• 1999

This paper presents a new approach for large-scale generator maintenance scheduling optimizations. The generator preventive maintenance scheduling problems are typical discrete dynamic n-dimensional vector optimization ones with several inequality constraints. The considered objective function to be minimized a subset of{{{{ { R}^{n } }}}} space is the variance (i.g., second-order momentum) of operating reserve margin to levelize risk or reliability during a year. By its nature of the objective function, the optimal solution can only be obtained by enumerating all combinatorial states of each variable, a task which leads to computational explosion in real-world maintenance scheduling problems. This paper proposes a new priority search mechanism based on each generator's discrete sensitivity value which was analytically developed in this study. Unlike the conventional capacity-based priority search, it can prevent the local optimal trap to some extents since it changes dynamically the search tree in each iteration. The proposed method have been applied to two test systems (i.g., one is a sample system with 10 generators and the other is a real-world lage scale power system with 280 generators), and the results anre compared with those of the conventional capacith-based search method and combinatorial optimization method to show the efficiency and effectiveness of the algorithm.

• 대한약학회:학술대회논문집
• /
• 대한약학회 2003년도 Proceedings of the Convention of the Pharmaceutical Society of Korea Vol.1
• /
• pp.69-71
• /
• 2003

As recent as 10 years ago, a method of developing new medicine was developed by a new compounding method moving away from an existing one. Combinatorial chemistry made it easier to combine various kinds of compounds in a very short time and with little effort from existing methods. Through combinatorial chemistry, a number of compounds were synthesized using HTS(High Throughput Screening), with many reports reaching a clinical stage in search of new candidate material. (omitted)

• Journal of Computing Science and Engineering
• /
• 제8권4호
• /
• pp.199-206
• /
• 2014

The ant colony optimization (ACO) algorithm is a new heuristic algorithm that offers good robustness and searching ability. With in-depth exploration, the ACO algorithm exhibits slow convergence speed, and yields local optimization solutions. Based on analysis of the ACO algorithm and the genetic algorithm, we propose a novel hybrid genetic ant colony optimization (NHGAO) algorithm that integrates multi-population strategy, collaborative strategy, genetic strategy, and ant colony strategy, to avoid the premature phenomenon, dynamically balance the global search ability and local search ability, and accelerate the convergence speed. We select the traveling salesman problem to demonstrate the validity and feasibility of the NHGAO algorithm for solving complex optimization problems. The simulation experiment results show that the proposed NHGAO algorithm can obtain the global optimal solution, achieve self-adaptive control parameters, and avoid the phenomena of stagnation and prematurity.

• 대한전기학회논문지:전력기술부문A
• /
• 제51권5호
• /
• pp.217-224
• /
• 2002

This paper presents an algorithm to obtain an approximate optimal solution for the service restoration and load balancing of large scale radial distribution system in a real-time operation environment. Since the problem is formulated as a combinatorial optimization problem, it is difficult to solve a large-scale combinatorial optimization problem accurately within the reasonable computation time. Therefore, in order to find an approximate optimal solution quickly, the authors proposed an algorithm which combines optimization technique called cyclic best-first search with heuristic based feeder loadings balance index for computational efficiency and robust performance. To demonstrate the validity of the proposed algorithm, numerical calculations are carried out the KEPCO's 108 bus distribution system.

• 한국경영과학회:학술대회논문집
• /
• 대한산업공학회/한국경영과학회 1995년도 춘계공동학술대회논문집; 전남대학교; 28-29 Apr. 1995
• /
• pp.891-895
• /
• 1995

This paper describes a solid modeling system based on a systematic description of techniques for analyzing and understanding on engineering drawings. Main stress is placed on clarifying the difference between the drawing understanding and the drawing recognition. The former, in which we feel major interest, is intrinsically a difficult problem because it inherent contains combinatorial search to require more than polynomial time. Actually, understanding drawings is regarded as a process to recover the information lost in projection 3-D objects to 2-D drawings. But, solid modeling by automatic understanding of the given drawings is one of the promising approach, which is described precisely in the text. Reviewing the studies performed so far, we summarize the future direction of the project and inevitable open problems left.

• 한국정보디스플레이학회:학술대회논문집
• /
• 한국정보디스플레이학회 2006년도 6th International Meeting on Information Display
• /
• pp.33-38
• /
• 2006

An evolutionary optimization process involving genetic algorithm and combinatorial chemistry was employed in an attempt to develop titanate-based red phosphors suitable for tri-color white light emitting diodes We screened a eight-cation oxide system including $(K,Li,Na)_x(Y,Gd,La,Eu)_yTi_zO_{\delta}$ in terms of luminescent efficiency. The combination of genetic algorithm and combinatorial chemistry was proven to enhance the searching efficiency when applied for phosphor screening. As a result, the composition was optimized to be $(Na_{0.92}Li_{0.08})(Y_{0.8}Gd_{0.2})TiO_4:Eu^{3+}$, The luminance of this phosphor was 110 % of that of well-known scheelite variant phosphor at an excitation of 400 nm.

• 한국세라믹학회지
• /
• 제37권2호
• /
• pp.134-139
• /
• 2000

The main objective of the present investigation is to show the feasibility of combinatorial chemistry by applying this method to phosphor syntehses. In this respect barium hexaaluminate phosphor was prepared by the split-pool combinatorial method, which enabled much more rapid search of optimum compositions of target phosphors than conventional synthetic methods. Barium hexaaluminate phosphors doped with Eu2+ exhibit blue emission while those co-doped with Mn2+ and Eu2+ exhibit green emission. Basically, the phosphor doped with 1.3 mole of Ba and 0.06~0.15 mole of Eu2+ exhibit the maximum value of emission intensity at 435${\mu}{\textrm}{m}$. Under the UV and VUV extitations, the barium hexaaluminate phosphor co-doped with Mn2+ and Eu2+ shows strong green emission.

• 대한산업공학회지
• /
• 제21권3호
• /
• pp.409-428
• /
• 1995

Job shop scheduling with m different machines and n different jobs is a NP-hard problem of combinatorial optimization. The purpose of the paper is to develop the heuristic method using tabu search for job shop scheduling to minimize makespan or mean flowtime. To apply tabu search to job shop scheduling problem, in this paper we propose the several move methods that employ insert moves in order to generate the neighbor solutions, and present the efficient rescheduling procedure that yields active schedule for a changed operation sequence by a move of operations. We also discuss the tabu search techniques of diversifying the search of solution space as well as the simple tabu search. By experiments, we find the appropriate tabu list size and tabu attributes, and analyze the proposed tabu search techniques with respect to the quality of solutions and the efforts of computation. The experimental results show that the proposed tabu search techniques using long-term memory function have the ability to search a good solution, and are more efficient in the mean flowtime minimization problem than in the makespan minimization.

• Structural Engineering and Mechanics
• /
• 제25권2호
• /
• pp.239-268
• /
• 2007

This paper deals with optimal stacking sequence design of laminate composite structures. The stacking sequence optimisation of laminate composites is formulated as a combinatorial problem and is solved using Simulated Annealing (SA), an algorithm devised based on inspiration of physical process of annealing of solids. The combinatorial constraints are handled using a correction strategy. The SA algorithm is strengthened by embedding Tabu search in order to prevent recycling of recently visited solutions and the resulting algorithm is referred to as tabu embedded simulated Annealing (TSA) algorithm. Computational performance of the proposed TSA algorithm is enhanced through cache-fetch implementation. Numerical experiments have been conducted by considering rectangular composite panels and composite cylindrical shell with different ply numbers and orientations. Numerical studies indicate that the TSA algorithm is quite effective in providing practical designs for lay-up sequence optimisation of laminate composites. The effect of various neighbourhood search algorithms on the convergence characteristics of TSA algorithm is investigated. The sensitiveness of the proposed optimisation algorithm for various parameter settings in simulated annealing is explored through parametric studies. Later, the TSA algorithm is employed for multi-criteria optimisation of hybrid composite cylinders for simultaneously optimising cost as well as weight with constraint on buckling load. The two objectives are initially considered individually and later collectively to solve as a multi-criteria optimisation problem. Finally, the computational efficiency of the TSA based stacking sequence optimisation algorithm has been compared with the genetic algorithm and found to be superior in performance.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2000년도 ITC-CSCC -1
• /
• pp.245-248
• /
• 2000

This paper proposes a cooperative parallel tabu search which incorporates with the historical information exchange among processors in addition to its own searching of each processor. We investigate the influence of our proposed cooperative parallel tabu search by comparison with a serial tabu search. We also propose two extensions of the cooperative parallel tabu search which are the cooperative construction of tabu memory and the selection of cooperative partner. Through computational experiment, we observe the improvement of solutions by our proposed method.