• Journal of Communications and Networks
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• 제16권3호
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• pp.293-300
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• 2014

As energy harvesting communication systems emerge, there is a need for transmission schemes that dynamically adapt to the energy harvesting process. In this paper, after exhibiting a finite-horizon online throughput-maximizing scheduling problem formulation and the structure of its optimal solution within a dynamic programming formulation, a low complexity online scheduling policy is proposed. The policy exploits the existence of thresholds for choosing rate and power levels as a function of stored energy, harvest state and time until the end of the horizon. The policy, which is based on computing an expected threshold, performs close to optimal on a wide range of example energy harvest patterns. Moreover, it achieves higher throughput values for a given delay, than throughput-optimal online policies developed based on infinite-horizon formulations in recent literature. The solution is extended to include ergodic time-varying (fading) channels, and a corresponding low complexity policy is proposed and evaluated for this case as well.

• 대한산업공학회지
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• 제25권4호
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• pp.466-475
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• 1999

A backward Dynamic Programming(DP) model for the optimal facility replacement decision problem during a finite planning horizon is presented. Multiple alternative challengers to a current defender are considered. All facilities are assumed to have finite service lives. The objective of the DP model is to maximize the profit over a finite planning horizon. As for the cost elements, purchasing cost, maintenance costs and repair costs as well as salvage value are considered. The time to failure is assumed to follow a weibull distribution and the maximum likelihood estimation of Weibull parameters is used to evaluate the expected cost of repair. To evaluate the revenue, the rate of operation during a specified period is employed. The cash flow component of each challenger can vary independently according to the time of occurrence and the item can be extended easily. The effects of inflation and the time value of money are considered. The algorithm is illustrated with a numerical example. A MATLAB implementation of the model is used to identify the optimal sequence and timing of the replacement.

• 산업경영시스템학회지
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• 제31권2호
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• pp.19-27
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• 2008

This paper addresses determining the location of the distribution centers in a discrete dynamic distribution system. In discrete and finite time horizon, the demands of retailers are dynamic for the periods. Some locations among the retailers can be chosen for the role of the distribution centers at the beginning of each period. The distribution centers have to be located at the location of minimizing logistics cost. Logistics cost factors are the operation cost and the fixed cost of distribution center, and the transportation cost. The distribution centers of minimizing sum of operation cost, fixed cost and transportation cost are determined among retailers in each period for the planning period. A mathematical model was formulated and a dynamic programming based algorithm was developed. A numerical example was shown to explain our problem.

• 대한산업공학회지
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• 제24권1호
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• pp.157-165
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• 1998

This paper considers the single-product production and transportation problem with discrete time, dynamic demand and finite time horizon, an extension of classical dynamic lot-sizing model. In the model, multiple freight container types are allowed as the transportation mode and each order (product) placed in a period is shipped immediately by containers in the period. Moreover, each container has type-dependent carrying capacity restriction and at most one container type is allowed in each shipping period. The unit freight cost for each container type depends on the size of its carrying capacity. The total freight cost is proportional to the number of each container type employed. Such a freight cost is considered as another set-up cost. Also, it is assumed in the model that production and inventory cost functions are dynamically concave and backlogging is not allowed. The objective of this study is to determine the optimal production policy and the optimal transportation policy simultaneously that minimizes the total system cost (including production cost, inventory holding cost, and freight cost) to satisfy dynamic demands over a finite time horizon. In the analysis, the optimal solution properties are characterized, based on which a dynamic programming algorithm is derived. The solution algorithm is then illustrated with a numerical example.

• 한국경영과학회지
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• 제34권3호
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• pp.71-84
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• 2009

This paper considers a remanufacturing and purchasing planning problem, in which either used products(or wastes) are remanufactured or remanufactured products(or final products) are purchased to satisfy dynamic demands of remanufactured products over a discrete and finite time horizon. Also, as remanufactured products are purchased more than or equal to a special quantity Q, a discount price policy is applied. The problem assumes that the related cost(remanufacturing and inventory holding costs of used products, and the purchasing and inventory holding costs of remanufactured products) functions are concave and backlogging is not allowed. The objective of this paper is to determine the optimal remanufacturing and purchasing policy that minimizes the total cost to satisfy dynamic demands of remanufactured products. This paper characterizes the properties of the optimal policy and then, based on these properties, presents a dynamic programming algorithm to find the optimal policy. Also, a network-based procedure is proposed for the case of a large quantity of low cost used products. A numerical example is then presented to demonstrate the procedure of the proposed algorithm.

• 대한산업공학회지
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• 제41권3호
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• pp.259-266
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• 2015

Among many energy resources, natural gas has recently received a remarkable amount of attention, particularly from the electrical generation industry. This is in part due to increasing shale gas production, providing an environment-friendly fossil fuel, and high risk of nuclear power. Because South Korea, the world's second largest LNG importing nation after Japan, has no international natural gas pipelines and relies on imports in the form of LNG, the natural gas has been traditionally procured by long term LNG contracts at relatively high price. Thus, there is a need of developing an Asian LNG trading hub, where LNG can be traded at more competitive spot prices. In a natural gas spot market, the amount of natural gas to be bought should be carefully determined considering a limited storage capacity and future pricing dynamics. In this work, the problem to find the optimal amount of natural gas in a spot market is formulated as a Markov decision process (MDP) in risk neutral environment and the optimal base stock policy which depends on a stage and price is established. Taking into account price and demand uncertainties, the basestock target levels are simply approximated from dynamic programming. The simulation results show that the basestock policy can be one of effective ways for procurement of LNG in a spot market.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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• pp.20-23
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• 1996

This paper deals with the flexible manipulator with rotational and translational degrees of freedom, which has an arm of time-varying length with the prismatic joint. The tracking control problem of the flexible manipulator is considered. First we design the controller of the 2-type robust servo system based on the finite horizon optimal control theory for the trajectory planned as a discontinuous velocity. Next, to reduce the tracking error, we use the method of the dynamic programming and of modifying the reference trajectory in time coordinate. The simulation results show that the dynamic modeling is adequate and that the asymptotic stabilization of the flexible manipulator is preserved in spite of nonlinear terms. The PTP control error has been reduced to zero completely, and the trajectory tracking errors are reduced sufficiently by the proposed control method.

• 대한산업공학회지
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• 제16권1호
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• pp.51-58
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• 1990

A deterministic capacity expansion planning model for a two-capacity type facility is analyzed to determine the sizes to be expanded in each period so as to supply the known demands for two distinct capacity type(product) on time and to minimize the total cost incurred over a finite planning horizon of T periods. The model assumes that capacity unit of the facility simultaneously serves a prespecified number of demand units of each capacity type, that capacity type 1 can be used to supply demands for capacity type 2, but that capacity type 2 can't be used to supply demands for capacity type 1. Capacity expansion and excess capacity holding cost functions considered are nondecreasing and concave. The structure of an optimal solution is characterized and then used in developing an efficient dynamic programming algorithm that finds optimal capacity planning policy.

• 대한산업공학회지
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• 제37권4호
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• pp.331-341
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• 2011

This paper considers an inbound lot-sizing and outbound dispatching problem for a single product in a thirdparty logistics (3PL) distribution center. Demands are dynamic and finite over the discrete time horizon, and moreover, each demand has a delivery time window which is the time interval with the dates between the earliest and the latest delivery dates All the product amounts must be delivered to the customer in the time window. Ordered products are shipped by multiple vehicle types and the freight cost is proportional to the vehicle-types and the number of vehicles used. First, we formulate a mixed integer programming model. Since it is difficult to solve the model as the size of real problem being very large, we design a conventional genetic algorithm with a local search heuristic (HGA) and an improved genetic algorithm called adaptive genetic algorithm (AGA). AGA spontaneously adjusts crossover and mutation rate depending upon the status of current population. Finally, we conduct some computational experiments to evaluate the performance of AGA with HGA.

• 산업경영시스템학회지
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• 제37권1호
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• pp.60-67
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• 2014

This paper considers an inbound ordering and outbound dispatching problem for multi-products and multi-vehicles in a third-party distribution center. The demands are dynamic over a discrete and finite time horizon, and replenishing orders are shipped in various transportation modes and the freight cost is proportional to the number of vehicles used. Any mixture of products is loaded onto any type of vehicles. The objective of the study is to simultaneously determine the inbound lot-sizes, the outbound dispatching sizes, and the types and numbers of vehicles used to minimize total costs, which consist of inventory holding cost and freight cost. Delivery time window is one of the general dispatching policies between a third-party distribution center and customers in practice. In the policy, each demand of product for a customer must be delivered within the time window without penalty cost. We derive mixed integer programming models for the dispatching policy with delivery time windows and on-time delivery dispatching policy, respectively and analyze the effect on a dispatching policy with delivery time windows by comparing with on-time delivery dispatching policy using various computational experiments.