Optimal inventory and dynamic admission policies for a retailer of seasonal products with affiliate programs and drop‐shipping

This article investigates the optimal inventory and admission policies for a “Clicks‐and‐Bricks” retailer of seasonal products that, in addition to selling through its own physical and online stores, also sells through third‐party websites by means of affiliate programs. Through postings on partners' webpages, an affiliate program allows a retailer to attract customers who would otherwise be missed. However, this retailer needs to pay a commission for each sale that originates from the website operators participating in the program. The retailer may also refer online orders to other sources (such as distributors and manufacturers) for fulfillment through a drop‐shipping agreement and thus earns commissions. This would be an option when, for example, the inventories at the physical stores were running low. Therefore, during the selling horizon, the retailer needs to dynamically control the opening/closing of affiliate programs and decide on the fulfillment option for online orders. On the basis of a discrete‐time dynamic programming model, the optimal admission policy of the retailer is investigated in this paper, and the structural properties of the revenue function are characterized. Numerical examples are given to show the revenue impact of optimal admission control. The optimal initial stocking decisions at the physical stores are also studied. © 2009 Wiley Periodicals, Inc. Naval Research Logistics 2009     

On online bin packing with LIB constraints

In many applications of packing, the location of small items below large items, inside the packed boxes, is forbidden. We consider a variant of the classic online one‐dimensional bin packing, in which items allocated to each bin are packed there in the order of arrival, satisfying the condition above. This variant is called online bin packing problem with LIB (larger item in the bottom) constraints. We give an improved analysis of First Fit showing that its competitive ratio is at most , and design a lower bound of 2 on the competitive ratio of any online algorithm. In addition, we study the competitive ratio of First Fit as a function of an upper bound (where d is a positive integer) on the item sizes. Our upper bound on the competitive ratio of First Fit tends to 2 as d grows, whereas the lower bound of two holds for any value of d. Finally, we consider several natural and well known algorithms, namely, Best Fit, Worst Fit, Almost Worst Fit, and Harmonic, and show that none of them has a finite competitive ratio for the problem. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009     

Scheduling a maintenance activity on parallel identical machines

We study a problem of scheduling a maintenance activity on parallel identical machines, under the assumption that all the machines must be maintained simultaneously. One example for this setting is a situation where the entire system must be stopped for maintenance because of a required electricity shut‐down. The objective is minimum flow‐time. The problem is shown to be NP‐hard, and moreover impossible to approximate unless P = NP. We introduce a pseudo‐polynomial dynamic programming algorithm, and show how to convert it into a bicriteria FPTAS for this problem. We also present an efficient heuristic and a lower bound. Our numerical tests indicate that the heuristic provides in most cases very close‐to‐optimal schedules. © 2008 Wiley Periodicals, Inc. Naval Research Logistics 2009     

基于小波游程编码的改进算法

提出一种基于小波和数学形态学的自适应游程编码的改进算法.与其他优秀的小波图像编码算法一样,自适应游程编码是一种对小波域经数学形态学处理得到的小波显著系数的有效编码方式.图像小波分解.经数学形态学膨胀处理后,位平面将出现大量极长的连"0",利用游程编码将是非常有效的.改进的自适应游程编码算法最突出的新特点是其可以将原始比特流转换成码长的二进制编码.实验结果表明,当连续码流相等的情况下,改进的算法可以有效减少编码长度.     

MABAC method for multiple attribute group decision making under q-rung orthopair fuzzy environment

As the generalization of intuitionistic fuzzy set (IFS) and Pythagorean fuzzy set (PFS), the q-rung orthopair fuzzy set (q-ROFS) has emerged as a more meaningful and effective tool to solve multiple attribute group decision making (MAGDM) problems in management and scientific domains. The MABAC (multi-attributive border approximation area comparison) model, which handles the complex and uncertain decision making issues by computing the distance between each alternative and the bored approximation area (BAA), has been investigated by an increasing number of researchers more recent years. In our article, consider the conventional MABAC model and some fundamental theories of q-rung orthopair fuzzy set (q-ROFS), we shall introduce the q-rung orthopair fuzzy MABAC model to solve MADM problems. at first, we briefly review some basic theories related to q-ROFS and conventional MABAC model. Furthermore, the q-rung orthopair fuzzy MABAC model is built and the decision making steps are described. In the end, An actual MADM application has been given to testify this new model and some comparisons between this novel MABAC model and two q-ROFNs aggregation operators are provided to further demonstrate the merits of the q-rung orthopair fuzzy MABAC model.     

On the reduction of total‐cost and average‐cost MDPs to discounted MDPs

This article provides conditions under which total‐cost and average‐cost Markov decision processes (MDPs) can be reduced to discounted ones. Results are given for transient total‐cost MDPs with transition rates whose values may be greater than one, as well as for average‐cost MDPs with transition probabilities satisfying the condition that there is a state such that the expected time to reach it is uniformly bounded for all initial states and stationary policies. In particular, these reductions imply sufficient conditions for the validity of optimality equations and the existence of stationary optimal policies for MDPs with undiscounted total cost and average‐cost criteria. When the state and action sets are finite, these reductions lead to linear programming formulations and complexity estimates for MDPs under the aforementioned criteria.© 2017 Wiley Periodicals, Inc. Naval Research Logistics 66:38–56, 2019     

Planning gamma accelerated degradation tests with two accelerating variables

Gamma accelerated degradation tests (ADT) are widely used to assess timely lifetime information of highly reliable products with degradation paths that follow a gamma process. In the existing literature, there is interest in addressing the problem of deciding how to conduct an efficient, ADT that includes determinations of higher stress‐testing levels and their corresponding sample‐size allocations. The existing results mainly focused on the case of a single accelerating variable. However, this may not be practical when the quality characteristics of the product have slow degradation rates. To overcome this difficulty, we propose an analytical approach to address this decision‐making problem using the case of two accelerating variables. Specifically, based on the criterion of minimizing the asymptotic variance of the estimated q quantile of lifetime distribution of the product, we analytically show that the optimal stress levels and sample‐size allocations can be simultaneously obtained via a general equivalence theorem. In addition, we use a practical example to illustrate the proposed procedure.     

Revenue management under randomly evolving economic conditions

We consider a dynamic pricing model in which the instantaneous rate of the demand arrival process is dependent on not only the current price charged by the concerned firm, but also the present state of the world. While reflecting the current economic condition, the state evolves in a Markovian fashion. This model represents the real‐life situation in which the sales season is relatively long compared to the fast pace at which the outside environment changes. We establish the value of being better informed on the state of the world. When reasonable monotonicity conditions are met, we show that better present economic conditions will lead to higher prices. Our computational study is partially calibrated with real data. It demonstrates that the benefit of heeding varying economic conditions is on par with the value of embracing randomness in the demand process. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 66:73–89,2019     

Dynamic routing of prioritized warranty repairs

Recent years have seen a strong trend toward outsourcing warranty repair services to outside vendors. In this article we consider the problem of dynamically routing warranty repairs to service vendors when warranties have priority levels. Each time an item under warranty fails, it is sent to one of the vendors for repair. Items covered by higher priority warranty receive higher priority in repair service. The manufacturer pays a fixed fee per repair and incurs a linear holding cost while an item is undergoing or waiting for repair. The objective is to minimize the manufacturer's long‐run average cost. Because of the complexity of the problem, it is very unlikely that there exist tractable ways to find the optimal routing strategies. Therefore, we propose five heuristic routing procedures that are applicable to real‐life problems. We evaluate the heuristics using simulation. The simulation results show that the index‐based “generalized join the shortest queue” policy, which applies a single policy improvement step to an initial state‐independent policy, performs the best among all five heuristics. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Scheduling and due‐date quotation in a make‐to‐order supply chain

We consider a manufacturer, served by a single supplier, who has to quote due dates to arriving customers in a make‐to‐order production environment. The manufacturer is penalized for long lead times and for missing due dates. To meet due dates, the manufacturer has to obtain components from a supplier. We model this manufacturer and supplier as a two‐machine flow shop, consider several variations of this problem, and design effective due‐date quotation and scheduling algorithms for centralized and decentralized versions of the model. We perform extensive computational testing to assess the effectiveness of our algorithms and to compare the centralized and decentralized models to quantify the value of centralized control in a make‐to‐order supply chain. Since complete information exchange and centralized control is not always practical or cost‐effective, we explore the value of partial information exchange for this system. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008