考虑相互信息监督下的服务合作生产契约

知识密集型服务合作生产由于存在相互之间的知识依赖和信息粘性,双方信息管理效率影响合作激励机制的设计。从相互信息监督视角出发,综合考虑双方信息监督效率和相对重要性参数对服务合作生产契约设计的影响。结果表明,在双方信息监督效率相同情况下,相对更重要的一方拥有剩余激励是最优的;在双方信息监督效率不同时,让监督更有效且相对更重要的一方拥有剩余激励是最优的;如果监督效率优势和相对重要性优势没有集中于一方,则结果取决于两者的比较,具有更强优势的一方应该成为剩余激励索取者。双方的相对重要性和信息监督效率共同决定合作契约。     

A robust optimization model for production planning of perishable products

In this study, a robust optimization model is developed to solve production planning problems for perishable products in an uncertain environment in which the setup costs, production costs, labour costs, inventory costs, and workforce changing costs are minimized. Using the concept of postponement, the production process for perishable products is differentiated into two phases to better utilize the resources. By adjusting penalty parameters, decision-makers can determine an optimal production loading plan and better utilize resources while considering different economic growth scenarios. A case from a Hong Kong plush toy company is studied and the characteristics of perishable products are discussed. Numerical results demonstrate the robustness and effectiveness of the proposed model. An analysis of the trade-off between solution robustness and model robustness is also presented.     

A General Pricing Scheme for the Simplex Method

In the simplex method for linear programming the algorithmic step of checking the reduced costs of nonbasic variables is called the “pricing” step. If these reduced costs are all of the “right sign” the current basis (and solution) is optimal, if not, this procedure selects a candidate vector that looks profitable for inclusion in the basis. While theoretically the choice of any profitable vector will lead to a finite termination (provided degeneracy is handled properly) but the number of iterations until termination depends very heavily on the actual choice (which is defined by the selection rule applied). Pricing has long been an area of heuristics to help make better selection. As a result, many different and sophisticated pricing strategies have been developed, implemented and tested. So far none of them is known to be dominating all others in all cases. Therefore, advanced simplex solvers need to be equipped with many strategies so that the most suitable one can be activated for each individual problem instance. In this paper we present a general pricing scheme. It creates a large flexibility in pricing. It is controlled by three parameters. With different settings of the parameters many of the known strategies can be reproduced as special cases. At the same time, the framework makes it possible to define new strategies or variants of them. The scheme is equally applicable to general and network simplex algorithms.     

An EOQ Model with Substitutions Between Products

In this paper, we present an economic order quantity (EOQ) model when two products are required, and one can be substituted for the other, if necessary, at a given unit cost. We consider three cases: (i) when there is no substitution between the products, (ii) when there is full substitution between the products, and (iii) when there is partial substitution between the products. In a deterministic setting with proportional substitution costs, we would expect to find full substitution or no substitution being optimal, depending on the cost parameters. However, we observe that full substitution is never optimal; only partial substitution or no substitution may be optimal. This result can best be explained due to the non-linearity of the decision variables in the total cost expression. Finally, we present an algorithm to compute the optimal order quantities.     

Optimal sales force compensation plans: an operational procedure

This paper describes an operational procedure for identifying optimal sales force compensation plans featuring salary, commissions and/or quota/bonus. Utility-maximising salespeople's behaviours and reactions to given compensation plans are simulated, and the resulting sales, costs and long-term expected profits are assessed. Then, a search technique attempts to identify the long-term profit-maximising compensation plan structure. Operationally, the simulation model parameters are calibrated so as to reflect those of an actual sales force, and consequently the optimal compensation scheme for this specific sales force can be identified. The concept is illustrated in an actual case study.     

An optimal production-inventory model for deteriorating items with multiple-market demand

The global markets of today offer more selling opportunities to the deteriorating items’ manufacturers, but also pose new challenges in production and inventory planning. From a production management standpoint, opportunities to exploit the difference in the timing of the selling season between geographically dispersed markets for deteriorating items are important to improving a firm’s profitability. In this paper, we examined the above issue with an insightful production-inventory model of a deteriorating items manufacturer selling goods to multiple-markets with different selling seasons. We also provided a solution procedure to find the optimal replenishment schedule for raw materials and the optimal production plan for finished products. A numerical example was then used to illustrate the model and the solution procedure. Finally, sensitivity analysis of the optimal solution with respect to major parameters was carried out.     

Optimal Control of Multigroup Neutron Fission Systems

This article considers the optimal control of nuclear fission reactors modeled by parabolic partial differential equations. The neutrons are divided into fast and thermal groups with two equations describing their interaction and fission, while a third equation describes the temperature in the reactor. The coefficient for the fission and absorption of the thermal neutron is assumed to be controlled by a function through the use of control rods in the reactor. The object is to maintain a target neutron flux shape, while a desired power level and adjustment costs are taken into consideration. A nonlinear optimality system of six equations is deduced, characterizing the optimal control. An iterative procedure is shown to contract toward the solution of the optimality system in small time intervals. The theory is extended to include the effect of other fission products, leading to coupled ordinary and partial differential equations. Numerical experiments are also included, suggesting directions for further research. Accepted 13 January 1998     

On the determination of the control parameters of the optimal can-order policy

This paper considers the well-known class of can-order policies. This type of coordinated replenishment policies accounts for a joint set-up cost structure, where a major set-up cost is incurred for any order and an individual minor set-up cost is charged for each item in the replenishment. Recent comparative studies have pointed out that the performance of the optimal can-order policy is poor, compared to other coordinated replenishment strategies, when the major set-up cost is high. This paper shows that it is the approximate decomposition method to calculate the optimal canorder parameters which performs bad in such situations and not the policy itself. Attention is focused to a subclass of can-order policies, which is close to the optimal can-order policy for high major set-up costs. A solution procedure is developed to calculate the optimal control parameters of this policy. It is shown that a properly chosen combination of the solution procedures to calculate can-order parameters leads to a can-order strategy which performs as well as other coordinated replenishment policies.     

Citizen coproduction and efficient public good provision: Theory and evidence from local public libraries

In both public administration and economics, efficiency is brought forward as an important criterion for evaluating administrative actions. Clearly, its value as an assessment principle depends on our ability to adequately measure efficiency. This article argues that citizen’s coproduction in public services requires a careful reassessment of how we approach the measurement of productive efficiency in public service delivery. Theoretically, we illustrate that using observable outcomes (e.g., library circulation, school results, health outcomes, fires extinguished, and crimes solved) as output indicators is inappropriate and leads to biased estimates of public service providers’ productive efficiency. This bias arises because citizens co-determine final outputs, leaving them at least partly beyond the service providers’ control. Empirically, we find supportive evidence of both the existence and importance of such ‘demand-induced’ bias.     

Optimizing costs of age replacement policies

This paper continues earlier work on the best implementation procedure for an age replacement policy. Under an age replacement policy, a stochastically failing unit is replaced at failure or after being in service for x units of time, whichever comes first. Sequentially estimating φ, the optimal replacement time, produces substantial cost savings. In this paper the rate of convergence of the actual costs to the theoretical optimal cost is studied. For any sequential procedure satisfying some mild measurability conditions, it is shown that with probability one the rate of convergence of the cost can be described based on the rate of convergence of the estimator of φ. Further, a sequential procedure is described whose cost converges to the optimal cost more rapidly than known competing procedures. For this procedure, the rate of convergence of the costs is further described by a result which states that an average actual cost per unit, when suitably standardized, converges in distribution to a normal random variable.     

The time-optimal transfer of a perturbed dynamical object to a given position

The problem of transferring a dynamical object (a point mass) of arbitrary dimensional to a required position in a time-optimal manner by means of a force of limited modulus is solved. The velocity of the object at the final instant is not specified. It is assumed that an arbitrary known perturbation, with a magnitude strictly less than that of the control, acts on the controlled system. For clarity when analysing the optimal controlled motion, considerable attention is paid to the case of a steady perturbation. A constructive procedure for finding the optimal response time and the control is developed for arbitrary permissible values of the governing parameters. The Bellman function and the feedback control are constructed over the whole of the phase space. The structural properties of the solution are established and an asymptotic analysis is carried out by small-parameter methods. The extremal directions of the perturbation vector and the corresponding response time and optimal control are found. A modification of the time-optimal problem to the case of a non-stationary perturbation is presented and the basic properties of the optimal solution are investigated.     

Determination/estimation of an optimal replacement interval under minimal repair

In this paper the problem of estimation of an optimal replacement interval for a system which is minimally repaired at failures is studied. The problem is investigated both under a parametric and a nonparametric form of the failure intensity of the system. It is assumed that observational data from n systems are available. Some asymptotic results are shown. A graphical procedure for determining/estimating an optimal replacement interval is presented. The procedure is particularly valuable for sensitivity analyses, for example with respect to the costs involved.     

A Markov Sensitivity Model for Examining the Impact of Cost Allocations in Hospitals

The cost allocation process in hospitals typically entails an accounting step-down procedure whereby costs are allocated from non-revenue producing service centres to revenue centres. The resulting revenue centre costs are then compared with the third party (Blue Cross, Medicare, Medicaid) allowable costs. Any costs in excess of the allowable costs are not reimbursable. This procedure has been conceptualized using a Markov chain in a recent journal article. The purpose of this paper is to demonstrate how the Markov model may be used to assess the impact of various changes in the original data without having to recalculate the entire step-down process via a Markov model or any other procedure. The changes include an alternate step-down model, a different cost allocation basis for one or more service centres, and the expansion or contraction of one or more service centres.     

Deterministic hierarchical substitution inventory models

In this paper, we consider a deterministic nested substitution problem where there are multiple products which can be substituted one for the other, if necessary, at a certain cost. We consider the case when there are n products, and product j can substitute products j + 1,…,n at certain costs. The trade-off is the cost of storing products (for example, customised products) at a higher inventory holding stage versus the cost of transferring downwards from a lower inventory holding cost (generic product) stage. The standard approach to solving the problem yields an intractable formulation, but by reformulating the problem to determine the optimal run-out times, we are able to determine the optimal order and substitution quantities. Numerical examples showing the effect of various system parameters on the optimal order and substitution policy are also presented.     

A flexible extended warranty and related optimal strategies

The choice of extended warranties (EWs) currently available to consumers is extremely limited. Their EW purchase decisions have to be made at or very close to the time that they purchase the products and, at this point, they are uncertain about item reliability, future operating costs, and usage time before replacement. In this paper, we discuss an EW that offers more flexibility and we investigate optimal pricing strategies for the EW provider and optimal maintenance and replacement strategies for the consumer.     

A simple procedure for determining order quantities under a fill rate constraint and normally distributed lead-time demand

One of the most common practical inventory control problems is considered. A single-echelon inventory system is controlled by a continuous review (R, Q) policy. The lead-time demand is normally distributed. We wish to minimize holding and ordering costs under a fill rate constraint. Although, it is not especially complicated to derive the optimal solution, it is much more common in practice to use a simple approximate two-step procedure where the order quantity is determined from a deterministic model in the first step. We provide an alternative, equally simple technique, which is based on the observation that the considered problem for each considered fill rate has a single parameter only. The optimal solution for a grid of parameter values is stored in a file. When solving the problem for an item we use interpolation, or for parameter values outside the grid special approximations. The approximation errors turn out to be negligible. As an alternative to the interpolation we also provide polynomial approximations.     

Response surface methodology: A neural network approach

Response surface methodology is used to optimize the parameters of a process when the function that describes it is unknown. The procedure involves fitting a function to the given data and then using optimization techniques to obtain the optimal parameters. This procedure is usually difficult due to the fact that obtaining the right model may not be possible or at best very time consuming.In this paper, a two-stage procedure for obtaining the best parameters for a process with an unknown model is developed. The procedure is based on implementing response surface methodology via neural networks. Two neural networks are trained: one for the unknown function and the other for derivatives of this function which are computed using the first neural network. These neural networks are then used iteratively to compute parameters for an equation which is ultimately used for optimizing the function. Results of some simulation studies are also presented.     

Optimal configuration of a decentralized, market-driven production/inventory system

Pull systems are inherently easier to implement on the shop-floor; however, they are quite difficult to plan and design for optimal operation, leaving little guidelines to system designers and practitioners. In this paper we use an effective and relatively fast numerical method to understand the optimal configuration of a multi-stage, multi-product, decentralized, market-driven production/inventory system that minimizes average inventory holding subject to a service level constraint through selection of various production and procurement control parameters. We have also conducted a number of numerical experiments to understand how the control policies respond to changes in the system parameters, such as the number of stages, system workload, demand arrival rates of products, and inventory holding costs.     

Determination of the optimal accelerated burn-in time under Arrhenius–Lognormal distribution assumption

Burn-in has been widely used as an effective procedure for screening out failed electronic products during the early-failure period, before shipment to the customers. Environmental stress such as temperature is increasingly being used to effectively shorten the burn-in time, and this method is usually called an accelerated burn-in test. When different stress levels are chosen for the burn-in operation, the burn-in times must be determined. An Arrhenius–Lognormal distribution can describe the lognormal lifetime of electronic products under different temperature levels. In this paper, the Arrhenius–Lognormal distribution and its mean residual life function are applied to the accelerated burn-in cost model, and a genetic algorithm is used to solve for the optimal burn-in time. We choose a real TFT–LCD module as an example, and determine its optimal accelerated burn-in time. A sensitivity analysis of the TFT–LCD module case shows the effect of model parameters on optimal burn-in time.     

Lot sizing for a single product recovery system with variable setup numbers

Inventory systems for joint remanufacturing and manufacturing have recently received considerable attention. In such systems, used products are collected from customers and are kept at the recoverable inventory warehouse for future remanufacturing. In this paper a production–remanufacturing inventory system is considered, where the demand can be satisfied by production and remanufacturing. The cost structure consists of the EOQ-type setup costs, holding costs and shortage costs. The model with no shortage case in serviceable inventory is first studied. The serviceable inventory shortage case is discussed next. Both models are considered for the case of variable setup numbers of equal sized batches for production and remanufacturing processes. For these two models sufficient conditions for the optimal type of policy, referring to the parameters of the models, are proposed.