Optimal operation of multireservoir power systems

The optimal monthly operating policy of a multireservoir hydroelectric power system is a stochastic nonlinear problem. This paper presents a new method for determining the optimal monthly operating policy of a power system ofn reservoirs in series on a river taking into account the stochasticity of the river flows. Functional optimization techniques and minimum-norm formulation have been used to find the optimal release policy of the system. Results for a numerical example composed of four reservoirs are presented.This work was supported by the National Research Council of Canada, Grant No. A4146.     

On optimal operating conditions for a data processing system: A stochastic approach

In this paper, we consider the problem of determining optimal operating conditions for a data processing system. The system is burned‐in for a fixed burn‐in time before it is put into field operation and, in field operation, it has a work size and follows an age‐replacement policy. Assuming that the underlying lifetime distribution of the system has a bathtub‐shaped failure rate function, the properties of optimal burn‐in time, optimal work size and optimal age‐replacement policy will be derived. It can be seen that this model is a generalization of those considered in the previous works, and it yields a better optimal operating conditions. This paper presents an analytical method for three‐dimensional optimization problem. An algorithm for determining optimal operating conditions is also given. Copyright © 2007 John Wiley & Sons, Ltd.     

Joint Distributions for Interacting Fluid Queues

Motivated by recent traffic control models in ATM systems, we analyse three closely related systems of fluid queues, each consisting of two consecutive reservoirs, in which the first reservoir is fed by a two-state (on and off) Markov source. The first system is an ordinary two-node fluid tandem queue. Hence the output of the first reservoir forms the input to the second one. The second system is dual to the first one, in the sense that the second reservoir accumulates fluid when the first reservoir is empty, and releases fluid otherwise. In these models both reservoirs have infinite capacities. The third model is similar to the second one, however the second reservoir is now finite. Furthermore, a feedback mechanism is active, such that the rates at which the first reservoir fills or depletes depend on the state (empty or nonempty) of the second reservoir.The models are analysed by means of Markov processes and regenerative processes in combination with truncation, level crossing and other techniques. The extensive calculations were facilitated by the use of computer algebra. This approach leads to closed-form solutions to the steady-state joint distribution of the content of the two reservoirs in each of the models.     

Optimally maintaining a Markovian deteriorating system with limited imperfect repairs

We consider the problem of optimally maintaining a periodically inspected system that deteriorates according to a discrete-time Markov process and has a limit on the number of repairs that can be performed before it must be replaced. After each inspection, a decision maker must decide whether to repair the system, replace it with a new one, or leave it operating until the next inspection, where each repair makes the system more susceptible to future deterioration. If the system is found to be failed at an inspection, then it must be either repaired or replaced with a new one at an additional penalty cost. The objective is to minimize the total expected discounted cost due to operation, inspection, maintenance, replacement and failure. We formulate an infinite-horizon Markov decision process model and derive key structural properties of the resulting optimal cost function that are sufficient to establish the existence of an optimal threshold-type policy with respect to the system’s deterioration level and cumulative number of repairs. We also explore the sensitivity of the optimal policy to inspection, repair and replacement costs. Numerical examples are presented to illustrate the structure and the sensitivity of the optimal policy.     

Optimal long-term operation of a multireservoir power system for critical water conditions

We present in this paper a new method for solving the optimization problem of a variable head multireservoir power system under a critical water condition for long-term regulation. The problem is formulated as a minimum norm problem. The proposed method is efficient in computing time and in calculating the expected benefits from the system during the critical period. Numerical results are presented for a real system in operation consisting of two rivers; each river has two reservoirs connected in a series.This work was supported by the National Research Council of Canada, Grant No. A4146. The authors wish to thank B. C. Hydro for providing the reservoir data.     

Flow regulation for water quality restoration in a river section: Modeling and control

This work is devoted to the numerical resolution of an optimal control problem that arises in the management of a reservoir for the remediation of a polluted river section. By using mathematical modeling and optimal control techniques we set the mathematical formulation of the problem (as a hyperbolic optimal control problem with control constraints), and obtain a fully discretized problem. Finally, we propose a gradient-free method to solve it, and present realistic numerical results.     

Liquidity risk and optimal dividend/investment strategies

In this paper, we study the problem of determining an optimal control on the dividend and investment policy of a firm operating under uncertain environment and risk constraints. We allow the company to make investment decisions by acquiring or selling producing assets whose value is governed by a stochastic process. The firm may face liquidity costs when it decides to buy or sell assets. We formulate this problem as a multi-dimensional mixed singular and multi-switching control problem and use a viscosity solution approach. We numerically compute our optimal strategies and enrich our studies with numerical results and illustrations.     

Periodic-Review Inventory Model with Three Consecutive Delivery Modes and Forecast Updates

This paper is concerned with a periodic-review inventory system with three consecutive delivery modes (fast, medium, and slow) and demand forecast updates. At the beginning of each period, the inventory level and demand information are updated and decisions on how much to order using each of the three delivery modes are made. It is shown that there is a base-stock policy for fast and medium modes which is optimal. Furthermore, the optimal policy for the slow mode may not be a base-stock policy in general.This research was supported in part by a Faculty Research Grant from the University of Texas at Dallas, a RGC (Hong Kong) Competitive Earmarked Research Grant, a Distinguished Young Investigator Grant from the National Natural Sciences Foundation of China, and a Grant from the Hundred Talents Program of the Chinese Academy of Sciences.     

Optimal production control of a dynamic two-product manufacturing system with setup costs and setup times

This paper deals with the optimal control of a one-machine two-product manufacturing system with setup changes, operating in a continuous time dynamic environment. The system is deterministic. When production is switched from one product to the other, a known constant setup time and a setup cost are incurred. Each product has specified constant processing time and constant demand rate, as well as an infinite supply of raw material. The problem is formulated as a feedback control problem. The objective is to minimize the total backlog, inventory and setup costs incurred over a finite horizon. The optimal solution provides the optimal production rate and setup switching epochs as a function of the state of the system (backlog and inventory levels). For the steady state, the optimal cyclic schedule is determined. To solve the transient case, the system's state space is partitioned into mutually exclusive regions such that with each region, the optimal control policy is determined analytically.     

PETROLEUM RESERVOIR MANAGEMENT: A RESERVOIR ECONOMIC APPROACH

This paper outlines an approach to investigate optimal depletion policies and economic policy issues for petroleum reservoirs. We integrate an economic understanding into the more detailed engineering studies and petroleum reservoir depletion technology. The paper quantifies the microeconomic adjustment of the exploitation of different types of petroleum reservoirs including the impact which economic parameters have on the resource recovery.     

Optimization of reservoirs in series on a river with a nonlinear storage curve for long-term regulation

We present in this paper a new approach to finding the monthly optimal operation of a multireservoir power system connected in series on a river. The hydroelectric power generation is a highly nonlinear function of the storage, and the conversion factor assigned to each power plant is also a nonlinear function of the storage. We use for both a quadratic function of the storage; the resulting problem has a highly nonlinear objective function and linear constraints. We propose a transformation such that the system equations are reduced to linear-quadratic form. Lagrange and Kuhn-Tucker multipliers are used to adjoin the equality and inequality constraints to the objective function. Numerical results are presented for a real system in operation consisting of two reservoirs in series on a river for widely different water conditions.This work was supported by the National Research Council of Canada, Grant No. A4146. The authors would like to acknowledge data obtained from B.C. Hydro.     

Component redundancy allocation in optimal cost preventive maintenance scheduling

This work presents a methodology to assist maintenance teams in defining the maintenance schedule and redundancy allocation that minimise the life-cycle average cost of a system. The minimal data required are three average costs and one reliability function. This methodology is useful in a system design phase, since in this situation data is usually scarce or inaccurate, but can also be applied in the exploration phase. It consists of an adaptation of the classical optimal age replacement method, combined with a redundancy allocation problem. A set of simple illustrative examples covering a variety of operating conditions is presented, demonstrating quantitatively the applicability of the methodology to a range of maintenance optimisation decisions.     

An application of the Fokker-Planck equation in stochastic reservoir theory

The distribution of the storage and of the outflow of a reservoir with a piecewise linear constant operating rule and Gaussian white-noise input is derived by analytically solving the Fokker-Planck equation. The proposed operating rule may approximate the well-known standard policy or, by increasing the number of intervals with constant outflow, may approximate the operating rule of existing reservoirs. The form of the solution renders possible the probabilistic analysis of the behavior of a water reservoir without numerical calculations.     

The Effect of Storage Carryover on Plant Expansion Planning

This paper considers the expansion of a river abstraction plant which is used conjunctively with a storage reservoir to supply water. Because of the uncertainty of inflows to the reservoir, the problem is stochastic and because of storage carryover from year to year, decisions on the plant size have a persistent effect. By assuming that the storage carryover effects last for a finite time only, the problem can be formulated in terms of a recurrence relation which can be solved by a version of dynamic programming. The optimality of the solution obtained is investigated by sensitivity testing.     

Peeling Layers of an Onion: Inventory Model with Multiple Delivery Modes and Forecast Updates

This paper is concerned with a periodic review inventory system with fast and slow delivery modes and regular demand forecast updates. At the beginning of each period, on-hand inventory and demand information are updated. At the same time, decisions on how much to order using fast and slow delivery modes are made. Fast and slow orders are delivered at the end of the current and the next periods, respectively. It is shown that there exists an optimal Markov policy and that it is a modified base-stock policy.     

On optimal polling policies

In a single-server polling system, the server visits the queues according to a routing policy and while at a queue, serves some or all of the customers there according to a service policy. A polling (or scheduling) policy is a sequence of decisions on whether to serve a customer, idle the server, or switch the server to another queue. The goal of this paper is to find polling policies that stochastically minimize the unfinished work and the number of customers in the system at all times. This optimization problem is decomposed into three subproblems: determine the optimal action (i.e., serve, switch, idle) when the server is at a nonempty queue; determine the optimal action (i.e., switch, idle) when the server empties a queue; determine the optimal routing (i.e., choice of the queue) when the server decides to switch. Under fairly general assumptions, we show for the first subproblem that optimal policies are greedy and exhaustive, i.e., the server should neither idle nor switch when it is at a nonempty queue. For the second subproblem, we prove that in symmetric polling systems patient policies are optimal, i.e., the server should stay idling at the last visited queue whenever the system is empty. When the system is slotted, we further prove that non-idling and impatient policies are optimal. For the third subproblem, we establish that in symmetric polling systems optimal policies belong to the class of Stochastically Largest Queue (SLQ) policies. An SLQ policy is one that never routes the server to a queue known to have a queue length that is stochastically smaller than that of another queue. This result implies, in particular, that the policy that routes the server to the queue with the largest queue length is optimal when all queue lengths are known and that the cyclic routing policy is optimal in the case that the only information available is the previous decisions.This work was supported in part by NSF under Contract ASC-8802764.     

Effects of system parameters on the optimal policy structure in a class of queueing control problems

This paper studies a class of queueing control problems involving commonly used control mechanisms such as admission control and pricing. It is well established that in a number of these problems, there is an optimal policy that can be described by a few parameters. From a design point of view, it is useful to understand how such an optimal policy varies with changes in system parameters. We present a general framework to investigate the policy implications of the changes in system parameters by using event-based dynamic programming. In this framework, the control model is represented by a number of common operators, and the effect of system parameters on the structured optimal policy is analyzed for each individual operator. Whenever a queueing control problem can be modeled by these operators, the effects of system parameters on the optimal policy follow from this analysis.      

Joint optimization of spare parts ordering and maintenance policies for multiple identical items subject to silent failures

In this paper the joint maintenance and spare parts ordering problem for more than one identical operating items is studied. The operating items may suffer two types of silent failures: a minor failure, which results in item malfunctioning, and a major failure, which renders the item completely out-of-function. Inspections are periodically held to detect any failures and the inspected items are preventively maintained, repaired or replaced according to their condition. Two ordering policies are investigated to supply the necessary spare parts: a periodic review and a continuous review policy. The expected total maintenance and inventory cost per time unit is derived and the proposed models are optimized for real case data. In addition, the sensitivity of the proposed models is studied through numerical examples and the effect of some key problem characteristics on the optimal decisions is discussed.     

Age-based vs. stock level control policies for a perishable inventory system

In this study, we investigate the impact of modified lotsize-reorder control policy for perishables which bases replenishment decisions on both the inventory level and the remaining lifetimes of items in stock. We derive the expressions for the key operating characteristics of a lost sales perishable inventory model, operating under the proposed age-based policy, and examine the sensitivity of the optimal policy parameters with respect to various system parameters. We compare the performance of the suggested policy to that of the classical (Q,r) type policy through a numerical study over a wide range of system parameters. Our findings indicate that the age-based policy is superior to the stock level policy for slow moving perishable inventory systems with high service levels.     

Transient and steady-state analysis of a manufacturing system with setup changes

This paper deals with the optimal scheduling of a one-machine two-product manufacturing system with setup, operating in a continuous time dynamic environment. The machine is reliable. A known constant setup time is incurred when switching over from a part to the other. Each part has specified constant processing time and constant demand rate, as well as an infinite supply of raw material. The problem is formulated as a production flow control problem. The objective is to minimize the sum of the backlog and inventory costs incurred over a finite planning horizon. The global optimal solution, expressed as an optimal feedback control law, provides the optimal production rate and setup switching epochs as a function of the state of the system (backlog and inventory levels). For the steady-state, the optimal cyclic schedule (Limit Cycle) is determined. This is equivalent to solving a one-machine two-product Lot Scheduling Problem. To solve the transient case, the system's state space is partitioned into mutually exclusive regions such that with each region is associated an optimal control policy. A novel algorithm (Direction Sweeping Algorithm) is developed to obtain the optimal state trajectory (optimal policy that minimizes the sum of inventory and backlog costs) for this last case.