• Industrial Engineering and Management Systems
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• v.11 no.2
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• pp.170-175
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• 2012

In this paper, a procedure using a genetic algorithm (GA) and a heuristic local search (HLS) is proposed for solving facility rearrangement problem (FRP). FRP is a decision problem for stopping/running of facilities and integration of stopped facilities to running facilities to maximize the production capacity of running facilities under the cost constraint. FRP is formulated as an integer programming model for maximizing the total production capacity under the constraint of the total facility operating cost. In the cases of 90 percent of cost constraint and more than 20 facilities, the previous solving method was not effective. To find effective alternatives, this solving procedure using a GA and a HLS is developed. Stopping/running of facilities are searched by GA. The shifting the production operation of stopped facilities into running facilities is searched by HLS, and this local search is executed for one individual in this GA procedure. The effectiveness of the proposed procedure using a GA and HLS is demonstrated by numerical experiment.

• Journal of Korean Association for Spatial Structures
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• v.3 no.4 s.10
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• pp.59-67
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• 2003

Genetic algorithm is one of the best ways to solve a discrete variable optimization problem. Genetic algorithm tends to thrive in an environment in which the search space is uneven and has many hills and valleys. In this study, genetic algorithm is used for solving the design problem of gable structure. The design problem of frame structure has some special features(complicate design space, many nonlinear constrants, integer design variables, termination conditions, special information for frame members, etc.), and these features must be considered in the formulation of optimization problem and the application of genetic algorithm. So, 'FRAME operator', a new genetic operator for solving the frame optimization problem effectively, is developed and applied to the design problem of gable structure. This example shows that the new opreator has the possibility to be an effective frame design operator and genetic algorithm is suitable for the frame optimization problem.

• Journal of Computational Design and Engineering
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• v.3 no.4
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• pp.295-311
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• 2016

This paper addresses to the flowshop scheduling problem with blocking constraints. The objective is to minimize the makespan criterion. We propose a hybrid combinatorial particle swarm optimization algorithm (HCPSO) as a resolution technique for solving this problem. At the initialization, different priority rules are exploited. Experimental study and statistical analysis were performed to select the most adapted one for this problem. Then, the swarm behavior is tested for solving a combinatorial optimization problem such as a sequencing problem under constraints. Finally, an iterated local search algorithm based on probabilistic perturbation is sequentially introduced to the particle swarm optimization algorithm for improving the quality of solution. The computational results show that our approach is able to improve several best known solutions of the literature. In fact, 76 solutions among 120 were improved. Moreover, HCPSO outperforms the compared methods in terms of quality of solutions in short time requirements. Also, the performance of the proposed approach is evaluated according to a real-world industrial problem.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.41
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• pp.231-242
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• 1997

This paper describe an approximation method for solving the minimum makespan problem of job shop scheduling with fuzzy processing time. We consider the multi-part production scheduling problem in a job shop scheduling. The job shop scheduling problem is a complex system and a NP-hard problem. The problem is more complex if the processing time is imprecision. The Fuzzy set theory can be useful in modeling and solving scheduling problems with uncertain processing times. Lee-Li fuzzy number comparison method will be used to compare processing times that evaluated under fuzziness. This study propose heuristic algorithm solving the job shop scheduling problem under fuzzy environment. In This study the proposed algorithm is designed to treat opinions of experts, also can be used to solve a job shop environment under the existence of alternate operations. On the basis of the proposed method, an example is presented.

• Journal of The Korean Association For Science Education
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• v.25 no.1
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• pp.1-15
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• 2005

This study examined two students' problem solving approaches: the similarities and the differences in their problem solving approaches, and the general problem solving strategies (heuristics) the students employed were discussed. The two students represent differences not only in terms of grades earned, but also in terms of participation, motivation, attention to detail, and approaches to answering questions and problem solving. Three separate problems were selected for this study: A stoichiometry problem; a fruit salad problem; and a limiting reactant problem. Each student was asked individually on three separate occasions to contribute to this study. There are more similarities in the students' problem solving strategies than there are differences. Both students were able to correctly solve the stoichiometry and the fruit salad problems, and were unable to correctly solve the limiting reactant problem. They recognized that an algorithm could be used for both chemistry problems(a stoichiometry problem & a limiting reactant problem). Both students were unable to correctly solve the limiting reactant problem and to demonstrate a clear understanding of the Law of Conservation of Mass. Nor did they show an ability to apply it in solving the problem. However, there was a difference in each one's ability to extend what had been learned/practiced/quizzed in class, to a related but different problem situation.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1149-1157
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• 2017

The satisfiability problem is always a core problem in artificial intelligence (AI). And how to improve the efficiency of algorithms solving the satisfiability problem is widely concerned. Algorithm IER (Improved Extension Rule) is based on extension rule. The number of atoms and the number of clauses affect the efficiency of the algorithm IER. DPLL rules are helpful to reduce these numbers. Then a complete algorithm CIER based on splitting rule and extension rule is proposed in this paper in order to improve the efficiency. At first, the algorithm CIER (Complete Improved Extension Rule) reduces the scale of a clause set with DPLL rules. Then, the clause set is split into a group of small clause sets. In the end, the satisfiability of the clause set is got from these small clause sets'. A strategy MOAMD (maximum occurrences and maximum difference) for the algorithm CIER is given. With this strategy, a better arrangement of atoms could be got. This arrangement could make the number of small clause sets fewer and the scale of these sets smaller. So, the algorithm CIER will be more efficient.

• The Journal of Korean Association of Computer Education
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• v.11 no.1
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• pp.85-95
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• 2008

The purpose of this study is to develop and apply the algorithm teaching materials centered on plays(ATMCP) to improve problem-solving abilities of elementary students. For this goal, the ATMCP were reviewed by the expert group and tested them out on 71 fifth-grade elementary students in Daegu, Korea during the 6 weeks. We divided students into two groups: one is the group of the ATMCP and the other is the group of conventional algorithm teaching materials(ATM). And we analyzed the change of the problem-solving ability of each group between before and after using two types of teaching materials with the Mixed ANOVA. The result showed that there was a significant difference in students' problem-solving abilities between before and after using them and the group of the ATMCP was greater improvement than the group of the conventional ATM in a problem-solving ability.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.49-58
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• 2019

Efficient evidential reasoning is an important issue in the development of advanced knowledge based systems. Efficiency is closely related to the design of problems solving methods adopted in the system. The explicit modeling of problem-solving structures is suggested for efficient and effective reasoning. It is pointed out that the problem-solving method framework is often too coarse-grained and too abstract to specify the detailed design and implementation of a reasoning system. Therefore, as a key step in developing a new reasoning scheme based on properties of the problem, the problem-solving method framework is expanded by introducing finer grained problem-solving primitives and defining an overall control structure in terms of these primitives. Once the individual components of the control structure are defined in terms of problem solving primitives, the overall control algorithm for the reasoning system can be represented in terms of a finite state diagram.

• Journal of applied mathematics & informatics
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• v.16 no.1_2
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• pp.337-354
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• 2004

SA, TS, GA and ACS are four of the main algorithms for solving challenging problems of intelligent systems. In this paper we consider Examination Timetabling Problem that is a common problem for all universities and institutions of higher education. There are many methods to solve this problem, In this paper we use Simulated Annealing, Tabu Search, Genetic Algorithm and Ant Colony System in their basic frameworks for solving this problem and compare results of them with each other.

• The Journal of Industrial Distribution & Business
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• v.10 no.11
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• pp.71-80
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• 2019

Purpose: The purpose of this study is to design the curriculum of Basic College Software Programming to develop creative and logical-thinking. This course is guided by algorithmic thinking and logical thinking that can be solved by computing for problem-solving, and it helps to develop by software through basic programming education. Through the stage of problem analysis, abstraction, algorithm, data structure, and algorithm implementation, the curriculum is designed to help learners experience algorithm problem-solving in various areas to develop diffusion thinking. For Learners aim to achieve the balanced development of divergent and convergent-thinking needed in their creative problem-solving skills. Research design, data and methodology: This study is to design a basic software education for improving algorithm-thinking for non-major. The curriculum designed in this paper is necessary to non-majors students who have completed the 'Creative Thinking and Coding Course' Design Thinking based are targeted. For this, contents were extracted through advanced research analysis at home and abroad, and experts in computer education, computer engineering, SW education, and education were surveyed in the form of quasi-openness. Results: In this study, based on ADD Thinking's algorithm thinking, we divided the unit college majors into five groups so that students of each major could accomplish the goal of "the ability to internalize their own ideas into computing," and extracted and designed different content areas, content elements and sub-components from each group. Through three expert surveys, we established a strategy for characterization by demand analysis and major/textbook category and verified the appropriateness of the design direction to ensure that the subjects and contents of the curriculum are appropriate for each family in order to improve algorithm-thinking. Conclusions: This study helps develop software by enhancing the ability of students who practice various subjects and exercises to explore creative expressions in various areas, such as 'how to think like a computer' that can implement and execute their ideas in computing. And it helps increase the ability to think logical and algorithmic computing based on creative solutions, improving problem-solving ability based on computing thinking and fundamental understanding of computer coding and development of logical thinking ability through programming.