Optimal multi-period mean–variance policy under no-shorting constraint

We consider in this paper the mean–variance formulation in multi-period portfolio selection under no-shorting constraint. Recognizing the structure of a piecewise quadratic value function, we prove that the optimal portfolio policy is piecewise linear with respect to the current wealth level, and derive the semi-analytical expression of the piecewise quadratic value function. One prominent feature of our findings is the identification of a deterministic time-varying threshold for the wealth process and its implications for market settings. We also generalize our results in the mean–variance formulation to utility maximization with no-shorting constraint.     

Optimal harvesting policy for a stochastic predator–prey model

Optimal harvesting of a stochastic predator–prey model is considered in this paper. Sufficient and necessary criteria for the existence of optimal harvesting strategy are obtained. At the same time, the optimal harvest effort and the maximum of sustainable yield are given.     

Single-manufacturer,multi-retailer consignment policy for retailers’ generalized demand distributions

Consignment policy (CP) is a novel approach to the inventory management in supply chains. It is based on strong interaction and reliable collaboration between vendor(s) and buyer(s), which is acquiring growing importance in today's industrial reality. Unlike most literature focusing on single-vendor single-buyer models and deterministic customer demand, a single-manufacturer (vendor) multi-retailer (buyer) generic model is developed under stochastic customer demand in this study. In order to understand the potential benefits of CP, it is compared with a traditional policy (TP) model developed in the similar approach. The models are tested with two scenarios of uniform and exponential demand distributions of the retailers. The results show how CP works better than the traditional uncoordinated optimization. It not only helps the manufacturer to generate higher profit, but also coordinates retailers to achieve a higher supply chain profit. At the same time, each retailer earns at least as much as they do in TP. Further price discount sensitivity analysis demonstrates the efficiency of CP when facing price-demand fluctuation.     

Time consistent behavioral portfolio policy for dynamic mean–variance formulation

When one considers an optimal portfolio policy under a mean-risk formulation, it is essential to correctly model investors’ risk aversion which may be time variant or even state dependent. In this paper, we propose a behavioral risk aversion model, in which risk aversion is a piecewise linear function of the current excess wealth level with a reference point at the discounted investment target (either surplus or shortage), to reflect a behavioral pattern with both house money and break-even effects. Due to the time inconsistency of the resulting multi-period mean–variance model with adaptive risk aversion, we investigate the time consistent behavioral portfolio policy by solving a nested mean–variance game formulation. We derive a semi-analytical time consistent behavioral portfolio policy which takes a piecewise linear feedback form of the current excess wealth level with respect to the discounted investment target. Finally, we extend the above results to time consistent behavioral portfolio selection for dynamic mean–variance formulation with a cone constraint.     

The superiority of “optimal control” over simulation in policy analysis

The simulation approach to policy analysis usually concentrates on policy multipliers as a measure of the thrust of economic policy. However, this measure is inadequate for one branch of economic policy, namely, fiscal policy. The reason is that the effectiveness of fiscal policy depends, via the government budget constraint, on the method of finance. It is argued in this paper that for this very reason the conventional way of calculating simulation-based dynamic multipliers introduces a bias towards the no-crowding-out thesis. This bias arises even in models of monetarist persuasion. Furthermore, it is shown that this bias can be removed by utilizing multipliers based on optimal control. We illustrate this proposition by providing numerical results using a large-scale U.K. econometric model of international monetarist persuasion (the London Business School model, LBS). Section 1 builds up a framework through which policy optimization can be compared and evaluated to policy simulations. In Section 2 we derive and compare policy multipliers obtained through policy simulations and optimal control. Section 3 provides a numerical example with the findings being summarized in Section 4.     

An optimal replenishment policy for an EOQ model with partial backlogging

We study an inventory system where demand on the stockout period is partially backlogged. The backlogged demand ratio is a mixture of two exponential functions. The shortage cost has two significant costs: the unit backorder cost (which includes a fixed cost and a cost proportional to the length of time for which the backorder exists) and the cost of lost sales. A general procedure to determine the optimal policy and the minimum inventory cost for all the parameter values is developed. This model generalizes several inventory systems analyzed by different authors. Numerical examples are used to illustrate the theoretical results.     

A single-vendor and multiple-buyers production–inventory policy for a deteriorating item

This study develops a single-vendor, multi-buyers production–inventory policy for a deteriorating item with a constant production and demand rate. A mathematical model incorporating the costs of both the vendor and the buyers is developed. It can be shown that the integrated policy results in an impressive cost reduction when it is compared with the independent decisions made by the vendor and the buyers.     

Patterns in the predator–prey system with network connection and harvesting policy

A diffusive predator–prey system with the network connection and harvesting policy is investigated in the present paper. The global existence and boundedness of the positive solutions to the parabolic equations are analyzed. Hereafter, a priori estimates and non-existence of the non-constant steady states are investigated for the corresponding elliptic equation. Next, we focus on the network connect model. The stability of the positive equilibrium, the Hopf bifurcation, and the Turing instability of networked system are explored. By using the multiple time scale (MTS), the direction of the Hopf bifurcation is determined. It is found that the networked system may admit a supercritical or subcritical Hopf bifurcation. For the Turing instability, the positive equilibrium will change its stability from an unstable state to a stable one with the change of the connecting probability. That is not the case in the model without network structure. Theoretical results also show that the model can create rich dynamical behaviors and numerical simulations well verify the validity of the theoretical analysis.     

The optimal ordering policy with trade credit under two different payment methods

Suppliers’ offering delay payment terms to retailers can be regarded as a type of price reduction. In today’s ever competitive marketplace, offering delay payments has become a commonly adopted method to suppliers. Most of the inventory models with permissible delay in payments assumed that the entire lot size is delivered at the same time. However, in practice, goods ordered are usually arrived overtime in separate batches. In this study, we discuss an inventory problem with a finite replenishment rate under trade credit for two payment methods. We establish a theorem to find the optimal solution for each payment method. Numerical examples are also given to illustrate the solution procedure. Finally, to investigate the effect of changes of some main parameter values on the optimal solution, a sensitivity analysis is performed and some management interpretations are proposed.     

An integrated inventory–transportation system with modified periodic policy for multiple products

Efficient management of a distribution system requires an integrated approach towards various logistical functions. In particular, the fundamental areas of inventory control and transportation planning need to be closely coordinated. Our model deals with an inbound material-collection problem. An integrated inventory–transportation system is developed with a modified periodic-review inventory policy and a travelling-salesman component. This is a multi-item joint replenishment problem, in a stochastic setting, with simultaneous decisions made on inventory and transportation policies. We propose a heuristic decomposition method to solve the problem, minimizing the long-run total average costs (major- and minor-ordering, holding, backlogging, stopover and travel). The decomposition algorithm works by using separate calculations for inventory and routing decisions, and then coordinating them appropriately. A lower bound is constructed and computational experience is reported.     

An optimal repair–replacement policy for a cold standby system with use priority

In this paper, the maintenance problem for a cold standby system consisting of two dissimilar components and one repairman is studied. Assume that both component 1 and component 2 after repair follow geometric process repair and component 1 is given priority in use when both components are workable. Under these assumptions, using geometric process repair model, we consider a replacement policy N under which the system is replaced when the number of failures of component 1 reaches N. Our purpose is to determine an optimal replacement policy N1 such that the average cost rate (i.e. the long-run average cost per unit time) of the system is minimized. The explicit expression for the average cost rate of the system is derived and the corresponding optimal replacement policy N1 can be determined analytically or numerically. Finally, a numerical example is given to illustrate some theoretical results and the model applicability.     

Start‐up class models in multiple‐class queues with N‐policy

In this paper, we consider multipleclass queueing systems with Npolicy in which the idle server starts service as soon as the number of customers in the startup class reaches threshold N. We consider the cases of FCFS and nonpreemptive priority. We obtain the Laplace–Stieltjes transform of the waiting times of each class of customers. We also show some results for the general behavior of such systems.     

Better than optimal mean–variance portfolio policy in multi-period asset–liability management problem

When the wealth is larger than some threshold in multi-period mean–variance asset–liability management, the pre-committed policy is no longer mean–variance efficient policy for the remaining investment horizon. To revise the policy, by relaxing self-financing constraint and allowing to withdraw some wealth, we derive a new dominating policy, which is better than the pre-committed policy. The revised policy can achieve the same mean–variance pairs attained by the pre-committed policy, and yields a nonnegative free cash flow stream over the investment horizon.     

Production–shipment policy for EPQ model with quality assurance and an improved delivery schedule

This article is concerned with determining the production–shipment policy for an economic production quantity model with quality assurance and an improved delivery schedule. We extend a recent work by Chiu et al. [Y.-S.P. Chiu, C.-A.K. Lin, H.-H. Chang, and V. Chiu, Mathematical modeling for determining economic batch size and optimal number of deliveries for EPQ model with quality assurance, Math. Comput. Model. Dyn. Sys. 16 (4) (2010), pp. 373–388] by incorporating an alternative delivery plan that aims at lowering the inventory holding cost for both supplier and buyer in such an integrated inventory system. Mathematical modelling along with Hessian matrix equations is used, and as a result the optimal production batch size and optimal number of deliveries are derived. A numerical example is provided to demonstrate the practical use of the results and the significant savings in stock holding costs for both vendor and buyer.     

When in a drug epidemic should the policy objective switch from use reduction to harm reduction?

A heated debate in drug policy concerns the relative merits of “harm reduction” (e.g., reducing drug-related HIV/AIDS transmission) vs. “use reduction” (controlling drug use per se). This paper models whether shifting emphasis between these goals over the course of a drug epidemic might reduce social costs relative to pursuing one or the other exclusively. Results suggest different answers for different drugs and/or countries. In particular, harm reduction may have always been effective for Australia’s injection drug use problem, but for US cocaine it may not have been in the past even if it could be so today. In certain circumstances harm reduction may “tip” an epidemic toward a high- rather than low-use equilibrium. The location in state space of regions where this occurs can be sensitive to parameter changes, suggesting caution may be in order when advocating harm reduction, unless there is confidence the epidemic has been modeled and parameterized accurately.     

Retailer’s optimal ordering policy for deteriorating items with maximum lifetime under supplier’s trade credit financing

Many products such as fruits, vegetables, pharmaceuticals, volatile liquids, and others not only deteriorate continuously due to evaporation, obsolescence, spoilage, etc. but also have their expiration dates (i.e., a deteriorating item has its maximum lifetime). Although numerous researchers have studied economic order quantity (EOQ) models for deteriorating items, few of them have taken the maximum lifetime of a deteriorating item into consideration. In addition, a supplier frequently offers her/his retailers a permissible delay in payments in order to stimulate sales and reduce inventory. There is no interest charge to a retailer if the purchasing amount is paid to a supplier within the credit period, and vice versa. In this paper, we propose an EOQ model for a retailer when: (1) her/his product deteriorates continuously, and has a maximum lifetime, and (2) her/his supplier offers a permissible delay in payments. We then characterize the retailer’s optimal replenishment cycle time. Furthermore, we discuss a special case for non-deteriorating items. Finally, we run several numerical examples to illustrate the problem and provide some managerial insights.     

Optimal pricing,shipment and payment policy for an integrated supplier–buyer inventory model with two-part trade credit

In this article, we develop an integrated supplier–buyer inventory model with the assumption that the market demand is sensitive to the retail price and the supplier adopts a trade credit policy. The trade credit policy discussed in this paper is a “two-part” strategy: cash discount and delayed payment. That is, if the buyer pays within M₁, the buyer receives a cash discount; otherwise, the full purchasing price must be paid before M₂, where _M2>_M1?0$M_2>M_1?0$. The objective of this research is to determine the optimal pricing, ordering, shipping, and payment policy to maximize the joint expected total profit per unit time. An iterative algorithm is established to obtain the optimal strategy. Furthermore, numerical examples and sensitivity analysis are presented to illustrate the results of the proposed model and to draw managerial insights.     

Optimal dividend policy when risk reserves follow a jump–diffusion process with a completely monotone jump density under Markov-regime switching

The paper studies optimal dividend distribution for an insurance company whose risk reserves in the absence of dividends follow a Markov-modulated jump–diffusion process with a completely monotone jump density where jump densities and parameters including discount rate are modulated by a finite-state irreducible Markov chain. The major goal is to maximize the expected cumulative discounted dividend payments until ruin time when risk reserve is less than or equal to zero for the first time. I extend the results of Jiang (2015) for a Markov-modulated jump–diffusion process from exponential jump densities to completely monotone jump densities by proving that it is also optimal to take a modulated barrier strategy at some positive regime-dependent levels and that value function as the fixed point of a contraction is explicitly characterized.     

Operational aspect of the policy coordination for financial stability: role of Jeffreys–Lindley’s paradox in operations research

This study analyses the implications of Jeffery–Lindley’s paradox and Global Financial Crisis (GFC) for the operational aspect of macroeconomic policy coordination for financial stability. Using a Bayesian Vector Auto-regressive model and data from Jan 1985 to June 2016, our key findings suggest that the claim of macroeconomic policy interaction, interdependence and significance of coordinated policy operations for the financial stability holds its ground. The argument in the support for policy coordination for financial stability was found to be robust against the Jeffreys–Lindley’s paradox and in the Post-GFC era. A profound practical, operational and philosophical implication of this study is the positive aspects of Jeffreys–Lindley’s paradox and the possibility of employing the Frequentist and Bayesian estimation techniques as complementing rather competing frameworks.

     

Efficient generation of alternative perspectives in public environmental policy formulation: applying co-evolutionary simulation–optimization to municipal solid waste management

In public policy formulation, it is generally preferable to create several quantifiably good alternatives that provide very different approaches to the particular situation. This is because public sector decision-making typically involves complex problems that are riddled with incompatible performance objectives and possess competing design requirements which are very difficult—if not impossible—to quantify and capture at the time supporting decision models are constructed. There are invariably unmodelled design issues, not apparent at the time of model construction, which can greatly impact the acceptability of the model’s solutions. Furthermore, public environmental policy formulation problems often contain considerable stochastic uncertainty and there are frequently numerous stakeholders with irreconcilable perspectives involved. Consequently, it is preferable to generate several alternatives that provide multiple, disparate perspectives to the problem. These alternatives should possess near-optimal objective measures with respect to the known modelled objective(s), but be fundamentally different from each other in terms of the system structures characterized by their decision variables. By generating a set of very different solutions, it is hoped that some of these dissimilar alternatives can provide very different perspectives that may serve to satisfy the unmodelled objectives. This study provides a co-evolutionary simulation–optimization modelling-to-generate-alternatives approach that can be used to efficiently create multiple solution alternatives that satisfy required system performance criteria in highly uncertain environments and yet are maximally different in their decision space. This new stochastic approach is very computationally efficient, since it permits the simultaneous generation of good solution alternatives in a single computational run of the SO algorithm. The efficacy and efficiency of this technique is specifically demonstrated using an earlier waste management case to enable direct comparisons to previous methods. Waste management systems provide an ideal setting for illustrating the modelling techniques used for such public environmental policy formulation, since they possess all of the prevalent incongruencies and system uncertainties inherent in complex planning processes.