• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1859-1864
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• 2004

An effective methodology is reported for the optimal design of multisite batch production/transportation and storage networks under uncertain demand forecasting. We assume that any given storage unit can store one material type which can be purchased from suppliers, internally produced, internally consumed, transported to or from other plant sites and/or sold to customers. We further assume that a storage unit is connected to all processing and transportation stages that consume/produce or move the material to which that storage unit is dedicated. Each processing stage transforms a set of feedstock materials or intermediates into a set of products with constant conversion factors. A batch transportation process can transfer one material or multiple materials at once between plant sites. The objective for optimization is to minimize the probability averaged total cost composed of raw material procurement, processing setup, transportation setup and inventory holding costs as well as the capital costs of processing stages and storage units. A novel production and inventory analysis formulation, the PSW(Periodic Square Wave) model, provides useful expressions for the upper/lower bounds and average level of the storage inventory. The expressions for the Kuhn-Tucker conditions of the optimization problem can be reduced to two sub-problems. The first yields analytical solutions for determining lot sizes while the second is a separable concave minimization network flow subproblem whose solution yields the average material flow rates through the networks for the given demand forecast scenario. The result of this study will contribute to the optimal design and operation of large-scale supply chain system.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.11
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• pp.956-962
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• 2005

This paper presents an integrated analysis of production and financing decisions. We assume that a cash storage unit is installed to manage the cash flows related with production activities such as raw material procurement, process operating setup, Inventory holding cost and finished product sales. Temporarily financial investments are allowed for more profit. The production plant is modeled by the Batch-Storage Network with Recycle Streams in Yi and Reklaitis (2003). The objective function of the optimization is minimizing the opportunity costs of annualized capital investment and cash/material inventory while maximizing stockholder's benefit. No depletion of all the material and cash storage units is major constraints of the optimization. A novel production and inventory analysis formulation, the PSW(Periodic Square Wave) model, provides useful expressions for the upper/lower bounds and average level of the cash and material inventory holdups. The expressions for the Kuhn-Tucker conditions of the optimization problem can be reduced to two subproblems and analytical lot sizing equations under a mild assumption about the cash flow pattern of stockholder's dividend. The first subproblem is a separable concave minimization network flow problem whose solution yields the average material flow rates through the networks. The second subproblem determines the decisions about financial Investment. Finally, production and financial transaction lot sizes and startup times can be determined by analytical expressions as far as the average flow rates are calculated. The optimal production lot and storage sizes considering financial factors are smaller than those without such consideration. An illustrative example is presented to demonstrate the results obtainable using this approach.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.6
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• pp.537-544
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• 2004

An effective methodology is reported for determining the optimal lot size of batch processing and storage networks which include uncertain demand forecasting. We assume that any given storage unit can store one material type which can be purchased from suppliers, internally produced, infernally consumed, transported to or from other sites and/or sold to customers. We further assume that a storage unit is connected to all processing and transportation stages that consume/produce or move the material to which that storage unit is dedicated. Each processing stage transforms a set of feedstock materials or intermediates into a set of products with constant conversion factors. A batch transportation process can transfer one material or multiple materials at once between sites. The objective for optimization is to minimize the probability averaged total cost composed of raw material procurement, processing setup, transportation setup and inventory holding costs as well as the capital costs of processing stages and storage units. A novel production and inventory analysis formulation, the PSW(Periodic Square Wave) model, provides useful expressions for the upper/lower bounds and average level of the storage inventory. The expressions for the Kuhn-Tucker conditions of the optimization problem can be reduced to two sub-problems. The first yields analytical solutions for determining lot sires while the second is a separable concave minimization network flow subproblem whose solution yields the average material flow rates through the networks for the given demand forecast scenario. The result of this study will contribute to the optimal design and operation of the global supply chain.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.34 no.8
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• pp.739-747
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• 2010

Numerical calculations are carried out for evaluating the natural convection induced by the temperature difference between a hot inner circular cylinder and a cold outer square enclosure. A two-dimensional solution for unsteady natural convection is obtained by using the finite volume method to model an inner circular cylinder that was designed by using the immersed boundary method (IBM) for a Rayleigh number of $10^7$. In this study, we investigate the effect of the location ($\delta$) of the inner cylinder, which is located along the vertical central axis of the outer enclosure, on the heat transfer and fluid flow. The natural convection changes from unsteady to steady state depending on the $\delta$. The two critical lower bound and upper bound positions are ${\delta}_{C,L}$ = 0.05 and ${\delta}_{C,U}$ = 0.18, respectively. Within these defined bounds, the thermal and flow fields are in steady state.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.305-312
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• 2010

The aim of this study is to find an analytic solution to the problem of determining the optimal capacity of a batch-storage network to meet demand for finished products in a system undergoing joint random variations of operating time and batch material loss. The superstructure of the plant considered here consists of a network of serially and/or parallel interlinked batch processes and storage units. The production processes transform a set of feedstock materials into another set of products with constant conversion factors. The final product demand flow is susceptible to joint random variations in the cycle time and batch size. The production processes have also joint random variations in cycle time and product quantity. The spoiled materials are treated through regeneration or waste disposal processes. The objective function of the optimization is minimizing the total cost, which is composed of setup and inventory holding costs as well as the capital costs of constructing processes and storage units. A novel production and inventory analysis the PSW (Periodic Square Wave) model, provides a judicious graphical method to find the upper and lower bounds of random flows. The advantage of this model is that it provides a set of simple analytic solutions while also maintaining a realistic description of the random material flows between processes and storage units; as a consequence of these analytic solutions, the computation burden is significantly reduced. The proposed method has the potential to rapidly provide very useful data on which to base investment decisions during the early plant design stage. It should be of particular use when these decisions must be made in a highly uncertain business environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3412-3432
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• 2019

Recent advances in radio frequency (RF) power transfer provide a promising technology to power sensor nodes. Adoption of mobile chargers to replenish the nodes' energy has recently attracted a lot of attention and the mobility assisted energy replenishment provides predictable and sustained power service. In this paper, we study the joint optimization of mobile charging and data gathering in sensor networks. A wireless multi-functional vehicle (WMV) is employed and periodically moves along specified trajectories, charge the sensors and gather the sensed data via one-hop communication. The objective of this paper is to maximize the uplink throughput by optimally allocating the time for the downlink wireless energy transfer by the WMV and the uplink transmissions of different sensors. We consider two scenarios where the WMV moves in a straight line and around a circle. By time discretization, the optimization problem is formulated as a 0-1 programming problem. We obtain the upper and lower bounds of the problem by converting the original 0-1 programming problem into a linear programming problem and then obtain the optimal solution by using branch and bound algorithm. We further prove that the network throughput is independent of the WMV's velocity under certain conditions. Performance of our proposed algorithm is evaluated through extensive simulations. The results validate the correctness of our proposed theorems and demonstrate that our algorithm outperforms two baseline algorithms in achieved throughput under different settings.

• Journal of Advanced Navigation Technology
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• v.26 no.6
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• pp.504-509
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• 2022

In this paper, we deal with the stability condition of linear time-varying interval discrete systems with time-varying delays and unstructured uncertainty. For the time-varying interval discrete system which has interval matrix as its system matrices, time-varying delay time within some interval value and unstructured uncertainty which can include non-linearity and be expressed by only its magnitude, the stability condition is proposed. Compared with the previous result derived by using a upper bound solution of the Lyapunov equation, the new result is derived by the form of simple inequality based on Lyapunov stability condition and has the advantage of being more effective in checking stability. Furthermore, the proposed condition is very comprehensive, powerful and inclusive the previously published conditions of various linear discrete systems, and can be expressed by the terms of magnitudes of the time-varying delay time and uncertainty, and bounds of interval matrices. The superiority of the new condition is shown in the derivation, and the usefulness and advantage of the proposed condition are examined through numerical example.

• Korean Chemical Engineering Research
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• v.46 no.3
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• pp.585-597
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• 2008

The aim of this study was to find an analytic solution to the problem of determining the optimal capacity (lot-size) of a batch-storage network to meet demand for a finished product in a system undergoing random failures of operating time and/or batch material. The superstructure of the plant considered here consists of a network of serially and/or parallel interlinked batch processes and storage units. The production processes transform a set of feedstock materials into another set of products with constant conversion factors. The final product demand flow is susceptible to short-term random variations in the cycle time and batch size as well as long-term variations in the average trend. Some of the production processes have random variations in product quantity. The spoiled materials are treated through regeneration or waste disposal processes. All other processes have random variations only in the cycle time. The objective function of the optimization is minimizing the total cost, which is composed of setup and inventory holding costs as well as the capital costs of constructing processes and storage units. A novel production and inventory analysis, the PSW (Periodic Square Wave) model, provides a judicious graphical method to find the upper and lower bounds of random flows. The advantage of this model is that it provides a set of simple analytic solutions while also maintaining a realistic description of the random material flows between processes and storage units; as a consequence of these analytic solutions, the computation burden is significantly reduced.