Collaborative supply chain planning under dynamic lot sizing costs with capacity decision

Studies show that supply chain cooperation improves supply chain performance. However, it remains a challenge to develop and implement the realistic supply chain cooperation scheme. We investigate a two-echelon supply chain planning problem with capacity acquisition decision under asymmetric cost and demand information. A simple negotiation-based coordination mechanism is developed to synchronize production/order strategies of a supplier and a buyer. The coordination scheme shows how the supplier and the buyer modify their production and order policy in order to find a joint economic lot sizing plan, which saves the overall supply chain cost. The allocation of the cooperation benefit is determined by negotiation. Due to the complexity of the multiple periods, multiple level supply chain lot sizing with capacity decision, a heuristic algorithm is developed to find coordination solutions. Finally, the results of the numerical study indicate the performance of supply chain coordination scheme.     

The distribution-free newsvendor problem with balking and penalties for balking and stockout

This paper investigates the ordering policy for the newsvendor problem with customer balking and penalties for balking and stockout. Our analysis is based on the assumption that only the mean and the variance of the demand distribution are known. In contrast to the existing research, we provide a new tradeoff tool as a replacement of the traditional one to weigh the holding cost and the goodwill cost segment： the balking penalty cost and the stockout penalty cost. Specifically, in addition to the stockout penalty, we also introduce the balking penalty, provide a new proof of the optimality of robust ordering policy to guarantee that the lower bound of expected profit obtained by us is tight, and get an robust optimal order quantity which is an exact solution but not an approximate one as before. Numerical experiments are conducted to illustrate the effect of penalties for balking and stockout.     

Coordinating pricing and inventory decisions in a bounded production system with uncertain yield

Most inventory researches assume that production level can fluctuate arbitrarily. However, large fluctuation of the production level in many firms may be much costly. This paper addresses the coordinating pricing and inventory control problem in a bounded production system with uncertain yield, in which the production level is constrained between a maximum and minimum level in each period and the price can be adjusted dynamically. We show that the optimal policy is the interval base-stock-list-price policy. Also, we study the impact of the production bounds and uncertainty of the yield on the production system. Numerical experiments are also performed to study the impact of parameters on the system.     

货架空间分配和库存控制联合优化策略研究

研究了需求率受展示空间影响的零售商品的货架空间分配和库存控制联合决策问题.针对各物品单独补货和多物品共同补货两种不同策略,分别建立了联合决策模型,分析了最优解的特性,并给出了共同补货模型的遍历搜索算法和两种近似求解算法.数值仿真研究表明:改进近似算法几乎达到了遍历搜索算法的效果,而近似算法在保证较好计算效果的基础上大大提高了计算效率;多物品共同补货与各物品单独补货策略相比,不仅改变了零售商的订购计划,也影响了其货架空间分配策略,并使零售商减少了库存,增加了利润;该模型也为零售商提供了比一些经验做法更优的货架空间分配策略.     

An optimal dynamic advertising model with inverse inventory sensitive demand effect for deteriorating items

This paper proposes a dynamic advertising model for deteriorating items, and the demand is influenced by goodwill and inventory level. The goodwill affected by advertising effort has a positive effect on demand while the inventory level has a negative effect on demand, which is named as inverse inventory sensitive demand effect. We assume that the deteriorating rate could be influenced by the inventory level and we determine the deteriorating rate formulation based on this assumption. The optimal advertising effort and inventory level are obtained by solving the optimization problem based on Pontryagin’s maximum principle. Furthermore, numerical studies are provided and some managerial insights are presented.     

The Center Problem and Time-Reversibility with Respect to a Quadratic Involution for a Class of Polynomial Differential Systems with Order 2 or 3

Journal of Systems Science and Complexity - Most studies of the time-reversibility are limited to a linear or an affine involution. In this paper, the authors consider the case of a quadratic...     

允许缺货和转包的受限批量模型的多项式算法

有效组织带转包的采购计划对企业提高竞争力和参与全球产业分工有重要意义.研究了一个新的非减库存能力约束下的允许缺货和转包的企业采购计划模型,提出了一个基于动态规划的多项式算法.引入子计划概念,将问题归结为有效计算子计划;依据最优解的性质设计了求解子计划的多项式算法;再通过动态规划算法以多项式时间枚举所有可能子计划组合,得到问题的最优解.数值试验显示了该算法的有效性及高效性.     

Heuristic algorithms for scheduling on uniform parallel machines with heads and tails

This paper considers the uniform parallel machine scheduling problem with unequal release dates and delivery times to minimize the maximum completion time.For this NP-hard problem,the largest sum of release date,processing time and delivery time first rule is designed to determine a certain machine for each job,and the largest difference between delivery time and release date first rule is designed to sequence the jobs scheduled on the same machine,and then a novel algorithm for the scheduling problem is built.To evaluate the performance of the proposed algorithm,a lower bound for the problem is proposed.The accuracy of the proposed algorithm is tested based on the data with problem size varying from 200 jobs to 600 jobs.The computational results indicate that the average relative error between the proposed algorithm and the lower bound is only 0.667%,therefore the solutions obtained by the proposed algorithm are very accurate.     

Optimal Decision Rule of the inventory Problem for Deteriorating items with Shortages and Time－varying Demand

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ADRC based input disturbance rejection for minimum-phase plants with unknown orders and/or uncertain relative degrees

The capability of ADRC is studied for linear time-invariant SISO minimum-phase systems with unknown orders,uncertain relative degrees,and unknown input disturbances.It is proved that ADRC can reject the unknown input disturbance and guarantee the close-loop stability for the plants with unknown but bounded relative degrees.Meanwhile,some close-loop performances can be achieved. The influence of the sensor noise is also discussed.And it is demonstrated by numerical examples that one ADRC with fixed parameters can be applied to a group of plants of different orders,relative degrees, and parameters.     

ON IMPROVING AN INTEGRATED INVENTORY MODEL FOR A SINGLE VENDOR AND MULTIPLE BUYERS WITH A RELAXED MATERIAL ORDERING CYCLE POLICY

1. Introduction With the development of information technology and the increasing market competition, simultaneously reducing inventory costs of raw materials, work-in-process, and finished items in different stages has become a major focus for supply chain management. Industrial practice and academic research have shown that VMI (Vendor Managed Inventory) can improve supply chain performance by decreasing inventory levels and costs. VMI is a collaborative business initiative where the vend…     

Semiparametric Bayesian inference for accelerated failure time models with errors-in-covariates and doubly censored data

This paper proposes a Bayesian semiparametric accelerated failure time model for doubly censored data with errors-in-covariates. The authors model the distributions of the unobserved covariates and the regression errors via the Dirichlet processes. Moreover, the authors extend the Bayesian Lasso approach to our semiparametric model for variable selection. The authors develop the Markov chain Monte Carlo strategies for posterior calculation. Simulation studies are conducted to show the performance of the proposed method. The authors also demonstrate the implementation of the method using analysis of PBC data and ACTG 175 data.     

Optimal risk control policies for diffusion models with non-cheap proportional reinsurance and bankruptcy value

This paper considers the problem about optimization of proportional reinsurance in the setting of diffusion models. The authors take into account non-cheap proportional reinsurance and bankruptcy value simultaneously. The objective is to find the risk control policies which maximize the total discounted reserve and the bankruptcy value. Results show that, the optimal risk control policies and corresponding optimal return functions vary, depending both on the range of bankruptcy value and the relationship between the premium rate of insurance and that of reinsurance.     

空调箱传感器故障在线检测和诊断新方法

针对空调箱的温度、流量等传感器进行固定偏差和漂移故障的检测与诊断,提出了一种基于统计学的方法进行在线的故障检测和诊断。主成分分析法根据系统正常的历史数据建立数理统计模型,通过传感器实际测量数据与正常数据在故障子空间投影的比较,对传感器的故障进行在线检测。联合角度法改进了传统的贡献图的诊断方法,通过对故障库中的故障知识的利用,能够在线的分离出发生故障的传感器。     

Concise review of relaxations and approximation algorithms for nonidentical parallel-machine scheduling to minimize total weighted completion times

A class of nonidentical parallel machine scheduling problems are considered in which the goal is to minimize the total weighted completion time. Models and relaxations are collected. Most of these problems are NP-hard, in the strong sense, or open problems, therefore approximation algorithms are studied. The review reveals that there exist some potential areas worthy of further research.     

延迟启动-关闭型的N-策略M/G/1排队系统队长分布

研究服务台具有延迟启动和延迟关闭的N-策略M/G/1排队系统,利用全概率分解技术,导出了任意时刻t瞬态队长分布的Laplace变换的递推关系式,进一步得到稳态队长分布的递推式以及平稳队长分布的随机分解.最后进行了数值实验,并考察了稳态队长分布以及附加队长分布的统计性质.     

EXPLORATION/EXPLOITATION TRADEOFF WITH CELL-SHIFT AND HEURISTIC CROSSOVER FOR EVOLUTIONARY ALGORITHMS

In order to tradeoff exploration/exploitation and inspired by cell genetic algorithm a cellshift crossover operator for evolutionary algorithm （EA） is proposed in this paper. The definition domain is divided into n-dimension cubic sub-domains （cell） and each individual locates at an ndimensional cube. Cell-shift crossover first exchanges the cell numbers of the crossover pair if they are in the different cells （exploration） and subsequently shift the first individual from its initial place to the other individual＇s cell place. If they are already in the same cell heuristic crossover （exploitation） is used. Cell-shift/heuristic crossover adaptively executes exploration/exploitation search with the vary of genetic diversity. The cell-shift EA has excellent performance in terms of efficiency and efficacy on ten usually used optimization benchmarks when comparing with the recent well-known FEP evolutionary algorithm.     

ANALYSIS AND COMPUTATIONAL ALGORITHM FOR QUEUES WITH STATE-DEPENDENT VACATIONS I： G/M（n）/1/K

In this paper we study a queueing system with state-dependent services and state-dependent vacations, or simply G/M（n）/1/K. Since the service rate is state-dependent, this system includes G/M/c and G/M/c/K queues with various types of station vacations as special cases. We provide a recursive algorithm using the supplementary variable technique to numerically compute the stationary queue length distribution of the system. The only input requirement is the Laplace-Stieltjes transform of the interarrival distribution as well as the state-dependent service rate and state-dependent vacation rate. In a subsequent companion paper, we study its dual system M（n）/G/1/K queue with statedependent vacations.     

ANALYSIS AND COMPUTATIONAL ALGORITHM FOR QUEUES WITH STATE-DEPENDENT VACATIONS II： M（n）/G/1/K

We study a single-server queueing system with state-dependent arrivals and general service distribution, or simply M（n）/G/1/K, where the server follows an N policy and takes multiple vacations when the system is empty. We provide a recursive algorithm using the supplementary variable technique to numerically compute the stationary queue length distribution of the system. The only input requirements are the Laplace-Stieltjes transforms of the service time distribution and the vacation time distribution, and the state-dependent arrival rate. The computational complexity of the algorithm is O（K^3）.     

A LAGRANGIAN RELAXATION APPROACH FOR SUPPLY CHAIN PLANNING WITH ORDER／SETUP COSTS AND CAPACITY CONSTRAINTS

A heuristic approach is developed for supply chain planning modeled as multi-item multi-levelcapacitated lot sizing problems. The heuristic combines Lagrangian relaxation(LR) with local search.Different from existing LR approaches that relax capacity constraints and/or inventory balanceconstraints, our approach only relaxes the technical constraints that each 0-1 setup variable must takevalue 1 if its corresponding continuous variable is positive. The relaxed problem is approximatelysolved by using the simplex algorithm for linear programming, while Lagrange multipliers are updatedby using a surrogate subgradient method that ensures the convergence of the dual problem in case ofthe approximate resolution of the relaxed problem. At each iteration, a feasible solution of the originalproblem is constructed from the solution of the relaxed problem. The feasible solution is furtherimproved by a local search that changes the values of two setup variables at each time. By taking theadvantages of a special stru