• 유통과학연구
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• 제15권2호
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• pp.15-20
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• 2017

Purpose - This paper aims to suggest a delivery constrained internet shopping optimization problem (DISOP) which must be solved for online recommendation system to provide a customized service considering cost and delivery conditions at the same time. Research design, data, and methodology - To solve a (DISOP), we propose a multi-objective formulation and a solution approach. By using a commercial optimization software (LINDO), a (DISOP) can be solved iteratively and a pareto optimal set can be calculated for real-sized problem. Results - We propose a new research problem which is different with internet shopping optimization problem since our problem considers not only the purchasing cost but also delivery conditions at the same time. Furthermore, we suggest a multi-objective mathematical formulation for our research problem and provide a solution approach to get a pareto optimal set by using numerical example. Conclusions - This paper proposes a multi-objective optimization problem to solve internet shopping optimization problem with delivery constraint and a solution approach to get a pareto optimal set. The results of research will contribute to develop a customized comparison and recommendation system to help more easy and smart online shopping service.

• 한국농공학회지
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• 제27권4호
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• pp.61-67
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• 1985

This study is concerned with the optimum design of reinforced concrete frame structure with multi-stories and multi-bays by Limit State Design Method aimed to establish a synthetical optimal method that can simultaneously acomplish structural analysis and sectional desig. For optimum solution, the Successive Linear Programming known as effective to nonlinear optimization problem: including both multi-design variables and mulit-constrained condition was applied. The developed algorithm was applied to an actual structure and reached following results. 1)The developed algorithm was rvey effective converging to an optimal solution with 3 to 5 iteration. 2)An optimal solution was showed when bending moment redistribution factor a was 0.80. 3)The column was, regardless of story, controlled by the long column when unbraced, while in case of braced column, it is designed with 3 short column controlled by thrust and bending moment, and the supporting condition had little effect on the optimization results.

• Journal of Astronomy and Space Sciences
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• 제25권3호
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• pp.255-266
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• 2008

The current paper presents application of a new analytic solution in general relative motion to spacecraft formation flying in an elliptic orbit. The calculus of variations is used to analytically find optimal trajectories and controls for the given problem. The inverse of the fundamental matrix associated with the dynamic equations is not required for the solution in the current study. It is verified that the optimal thrust vector is a function of the fundamental matrix of the given state equations. The cost function and the state vector during the reconfiguration can be analytically obtained as well. The results predict the form of optimal solutions in advance without having to solve the problem. Numerical simulation shows the brevity and the accuracy of the general analytic solutions developed in the current paper.

• 한국국방경영분석학회지
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• 제31권1호
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• pp.107-121
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• 2005

In this study, a new fictitious play (FP) procedure is presented to solve two-person zero-sum (TPZS) Blotto games. The FP solution procedure solves TPZS games by assuming that the two players take turns selecting optimal responses to the opponent's strategy observed so far. It is known that FP converges to an optimal solution, and it may be the only realistic approach to solve large games. The algorithm uses dynamic programming (DP) to solve FP subproblems. Efficiency is obtained by limiting the growth of the DP state space. Blotto games are frequently used to solve simple missile defense problems. While it may be unlikely that the models presented in this paper can be used directly to solve realistic offense and defense problems, it is hoped that they will provide insight into the basic structure of optimal and near-optimal solutions to these important, large games, and provide a foundation for solution of more realistic, and more complex, problem

• 한국CDE학회논문집
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• 제4권3호
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• pp.259-268
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• 1999

In order to reduce the cost of product and save the processing time, optimal nesting of two-dimensional part is an important application in number of industries like shipbuilding and garment making. There have been many studies on finding the optimal solution of two-dimensional nesting. The problem of two-dimensional nesting has a non-deterministic characteristic and there have been various attempts to solve the problem by reducing the size of problem rather than solving the problem as a whole. Heuristic method and linearlization are often used to find an optimal solution of the problem. In this paper, theoretical and practical nesting algorithm for rectangular, circular and irregular shape of two-dimensional parts is proposed. Both No-Fit-Polygon and Minkowski-Sum are used for solving the overlapping problem of two parts and the dynamic programming technique is used for reducing the number search spae in order to find an optimal solution. Also, nesting designer's expertise is complied into the proposed algorithm to supplement the heuristic method.

• 한국경영과학회지
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• 제28권2호
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• pp.129-138
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• 2003

The traveling salesman problem (TSP) is an NP-hard problem. As the number of nodes increases, it takes a lot of time to find an optimal solution. Instead of considering all arcs, if we select and consider only some arcs more likely to be included in an optimal solution, we can find efficiently an optimal solution. Arc candidate set is a group of some good arcs. For the Lack of study in the asymmetric TSP. it needs to research arc candidate set for the asymmetric TSP systematically. In this paper, we suggest a regression function determining arc candidate set for the asymmetric TSP. We established the function based on 2100 experiments, and we proved the goodness of fit for the model through various 787problems. The result showed that the optimal solutions obtained from our arc candidate set are equal to the ones of original problems. We expect that this function would be very useful to reduce the complexity of TSP.

• Journal of applied mathematics & informatics
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• 제28권5_6호
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• pp.1249-1262
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• 2010

An approximate alternating linearization decomposition method, for minimizing the sum of two convex functions with some separable structures, is presented in this paper. It can be viewed as an extension of the method with exact solutions proposed by Kiwiel, Rosa and Ruszczynski(1999). In this paper we use inexact optimal solutions instead of the exact ones that are not easily computed to construct the linear models and get the inexact solutions of both subproblems, and also we prove that the inexact optimal solution tends to proximal point, i.e., the inexact optimal solution tends to optimal solution.

• 한국경영과학회지
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• 제16권1호
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• pp.89-96
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• 1991

When a feasible solution approaches to the optimal extreme point in Karmakar's algorithm, components of the search direction vector for a solution converge at a certain value according to the corresponding columns of the optimal basis and the optimal nonbasis. By using this convergence properties of Karmarkar's algorithm, we can identify columns of the optimal basis before the final stage of the algorithm. The complexity of Karmarker's algorithm with newly proposed termination criterion does not increase. A numerical experiments for the problems which were generated by random numbers are also illustrated. Experimental results show that the number of iterations required for determining columns of the optimal basis depends on problems. For all cases, however, columns of the optimal basis are exactly verified when this termination criterion is used.

• International Journal of Control, Automation, and Systems
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• 제1권3호
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• pp.358-367
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• 2003

We consider discrete-time factorial Markov Decision Processes (MDPs) in multiple decision-makers environment for infinite horizon average reward criterion with a general joint reward structure but a factorial joint state transition structure. We introduce the "localization" concept that a global MDP is localized for each agent such that each agent needs to consider a local MDP defined only with its own state and action spaces. Based on that, we present a gradient-ascent like iterative distributed algorithm that converges to a local optimal solution of the global MDP. The solution is an autonomous joint policy in that each agent's decision is based on only its local state.cal state.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.25-29
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• 2003

LQ actuator selection problem for multi-input system discussed in this paper is to determine optimal actuator out of many actuators and input sequences so as to minimize the quadratic control performance. The solution of this problem depends on initial values and has a combinatorial property, so it is extremely difficult to get an optimal solution. For this difficulty, we proposed the concept of comparability of actuators and showed the uniqueness of the solution[1] . Further, to get general optimal solution for LQ problem with actuator selection strategies, we derived the equivalent condition for the comparability of actuator in single-input system . In this paper we extend this result to the case of multi-input system. The derived sufficient condition is applicable in the case of positive semi-definite comparability matrices.