• Journal of the Chungcheong Mathematical Society
• /
• v.27 no.2
• /
• pp.219-225
• /
• 2014

I use the dynamic programming approach to study the optimal consumption and investment problem with regime-switching and constant labor income. I derive the optimal solutions in closed-form with constant absolute risk aversion (CARA) utility and constant disutility.

• Magazine of the Korean Society of Agricultural Engineers
• /
• v.39 no.2
• /
• pp.1-8
• /
• 1997

Abstract The need for integrated reservoir system operation become more intense as the demands from the system increase. A deterministic, three-dimensional discrete incremental dynamic programming approach is presented to derive reservoirs system operational planning strategies. The developed H3DP model optimizes the monthly operation of the Hwachon and Soyang Projects on the North Han river and Chungju Main Project on the South Han river. By using the H3DP model, Hwachon project was reevaluated as a component of the upstream multipurpose storage reservoirs in the basin based on 1993 hydrology. This case study demonstrates the practical use of the developed model for the basin multi-reservoir system operation in an integrated, multipurpose fashion.

• Journal of Korean Institute of Industrial Engineers
• /
• v.5 no.1
• /
• pp.67-82
• /
• 1979

For many capacity expansion problems, distinct capacity types must be specified to identify capacity at different locations or capacities with different costs and operating characteristics. In this study, a project-sequencing model is developed that allows operating costs to influence the timing decisions for project establishment. Under certain conditions, the power expansion formulation is derived that may be solved through the dynamic programming approach, and its first application to planning in electric power systems is selected to investigate an optimal policy and to show the impact of requiring system to service more than one type of demand. Several sample testing results indicate that in some systems the efficiency of the large nuclear plants is higher than that of smell ones that it may overcome the effects of the drop in reliability.

• IE interfaces
• /
• v.24 no.3
• /
• pp.173-186
• /
• 2011

In this paper, we evaluate life annuity plans for Korean pre-retired single and married couple participating Korea National Pension (KNP) and find optimal life annuity strategy by using utility-based measurements called AEW (Annuity Equivalent Wealth). Specifically, we extend a previous study to obtain a detailed optimal combination of annuitizing age and wealth in terms of percentage of net wealth at the time of retirement. A nonlinear optimization model is formulated with the objective of maximizing utility on consumption and bequest, and the dynamic programming (DP) technique is used to solve this problem. We find that there exist consistent patterns in optimal combinations of annuitizing age and wealth. Also, for all cases the optimal combination is significantly better than several other combinations. The results indicate that using the optimal approach can be beneficial to practitioners in insurance industry and prospective purchasers of life annuity. We conclude the paper with some discussions and suggestions.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.15 no.1
• /
• pp.83-97
• /
• 1990

We consider an insured who wishes to determine his optimal reporting strategy over a given planning horizon, when he has option of reporting of not reporting his at-fault accidents. Assuming that the premium in future period is continually adjusted by the insured's loss experience, the insured would not report every loss incurred. Rather, considering the benefits and costs of each decision, the insured may want to seek a way of optimizing his interests over the planning horizon. The situation is modeled as a dynamic programming problem. We consider an insured's discounted expected cost minimization problem, where the premium increase in future period is affected by the size of the current claim. More specifically, we examine two cases ; (1) the premium increase in the next is a linear function (a constant fraction) of the current claim size; (2) the premium increase in the next period is a concave function of the current claim size. In each case, we derive the insured's optimal reporting strategy.

• Proceedings of the KIEE Conference
• /
• 1998.07c
• /
• pp.1140-1142
• /
• 1998

This paper presents object-oriented dynamic programing formulation of the unit commitment problem. This approach features the classification of generating units into related groups so called class. All object which share the same set of attributes and methods are grouped together in classes and designed inheritance hierarchy to minimize the number of unit combination which must be tested without precluding the optimal path. So this programming techniques will maximize the efficiency of unit commitment.

• Journal of Korea Society of Industrial Information Systems
• /
• v.17 no.6
• /
• pp.41-50
• /
• 2012

This paper presents a new sequence alignment method using the divide approach, which solves the problem by decomposing sequence alignment into several sub-alignments with respect to exact matching subsequences. Exact matching subsequences in the proposed method are bounded on the generalized suffix tree of two sequences, such as protein domain length more than 7 and less than 7. Experiment results show that protein sequence pairs chosen in PFAM database can be aligned using this method. In addition, this method reduces the time about 15% and space of the conventional dynamic programming approach. And the sequences were classified with 94% of accuracy.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.12 no.2
• /
• pp.5-20
• /
• 1987

This paper addresses sensitivity analysis for a deterministic multi-period production and inventory model. The model assumes a piecewise linear cost structure, but permits backlogging of unsatisfied demand. Our approach to sensitivity analysis here can be divided into two basic steps; (1) to find the optimal production policy through a forward dynamic programming algorithm similar to the backward version of Zangwill [1966] and (2) to apply the penalty network approach by the author [1986] in order to derive sensitivity ranges for various model parameters. Computational aspects are discussed and topics of further research are suggested.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.10
• /
• pp.3810-3830
• /
• 2015

In this paper, we investigate the differential game theoretic approach for distributed dynamic cooperative power control in cognitive radio ad hoc networks (CRANETs). First, a payoff function is defined by taking into consideration the tradeoff between the stock of accumulated power interference to the primary networks and the dynamic regulation of the transmit power of secondary users (SUs). Specifically, the payoff function not only reflects the tradeoff between the requirement for quickly finding the stable available spectrum opportunities and the need for better channel conditions, but also reveals the impact of the differentiated types of data traffic on the demand of transmission quality. Then the dynamic power control problem is modeled as a differential game model. Moreover, we convert the differential game model into a dynamic programming problem to obtain a set of optimal strategies of SUs under the condition of the grand coalition. A distributed dynamic cooperative power control algorithm is developed to dynamically adjust the transmit power of SUs under grand coalition. Finally, numerical results are presented to demonstrate the effectiveness of the proposed algorithm for efficient power control in CRANETs.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2002.05a
• /
• pp.179-184
• /
• 2002

We consider the heterogeneous fleet vehicle routing problem (HVRP), a variant of the classical vehicle routing problem (VRP). The HVRP differs from the classical VRP in that it deals with a heterogeneous fleet of vehicles having various capacities, fixed costs, and variables costs. Therefore the HVRP is to find the fleet composition and a set of routes with minimum total cost. We give an integer programming formulation of the problem and propose an algorithm to solve it. Although the formulation has exponentially many variables, we can efficiently solve the linear programming relaxation of it by using the column generation technique. To generate profitable columns we solve a shortest path problem with capacity constraints using dynamic programming. After solving the linear programming relaxation, we apply a branch-and-bound procedure. We test the proposed algorithm on a set of benchmark instances. Test results show that the algorithm gives best-known solutions to almost all instances.