Optimizing the pricing and replenishment policy for non-instantaneous deteriorating items with stochastic demand and promotional efforts

Retailer promotional activity has become prevalent in the business world. Promotional efforts impact the replenishment policy and the sale price of goods. In this paper, the problem of replenishment policy and pricing for non-instantaneous deteriorating items subject to promotional effort is considered. We adopt a price dependent stochastic demand function in which shortages are allowed and partially backlogged. The major objective is to simultaneously determine the optimal selling price, the optimal replenishment schedule, and the optimal order quantity to maximize the total profit. First, we prove that a unique optimal replenishment schedule exists for any given selling price. Second, we prove that the total profit is a concave function of price. Third, we present an algorithm to obtain the optimal solution and solve a numerical example. Last, we extend the numerical example by performing a sensitivity analysis of the model parameters and discuss specific managerial insights.     

A two stage heuristic algorithm for the integrated aircraft and crew schedule recovery problems

Airline disruptions incurred huge cost for airlines and serious inconvenience for travelers. In this paper, we study the integrated aircraft and crew schedule recovery problem. A two stage heuristic algorithm for the integrated recovery problem is proposed. In the first stage, the integrated aircraft recovery and flight-rescheduling model with partial crew consideration is built. This model is based on the traditional multi-commodity network model for the aircraft schedule recovery problem. The objective of this model also includes minimization of the original crew connection disruption. In the second stage, the integrated crew schedule recovery and flight re-scheduling model with partial aircraft consideration is built. We proposed a new multi-commodity model for the crew schedule recovery. The main advantage of such model is that it is much more efficient to integrate the flight-scheduling and aircraft consideration. New constraints are incorporated to guarantee that the aircraft connections generated in the stage 1 are still feasible. Two stages are run iteratively until no improvement can be achieved. Experimental results show that our method can provide better recovery solutions compared with the benchmark algorithms.     

Logistical support scheduling under stochastic travel times given an emergency repair work schedule

Stochastic factors during the operational stage could have a significant influence on the planning results of logistical support scheduling for emergency roadway repair work. An optimal plan might therefore lose its optimality when applied in real world operations where stochastic disturbances occur. In this study we employ network flow techniques to construct a logistical support scheduling model under stochastic travel times. The concept of time inconsistency is also proposed for precisely estimating the impact of stochastic disturbances arising from variations in vehicle trip travel times during the planning stage. The objective of the model is to minimize the total operating cost with an unanticipated penalty cost for logistical support under stochastic traveling times in short term operations, based on an emergency repair work schedule, subject to related operating constraints. This model is formulated as a mixed-integer multiple-commodity network flow problem and is characterized as NP-hard. To solve the problem efficiently, a heuristic algorithm, based on problem decomposition and variable fixing techniques, is proposed. A simulation-based evaluation method is also presented to evaluate the schedules obtained using the manual method, the deterministic model and the stochastic model in the operation stage. Computational tests are performed using data from Taiwan’s 1999 Chi-Chi earthquake. The preliminary test results demonstrate the potential usefulness of the proposed stochastic model and solution algorithm in actual practice.     

基于弹性客流的城市轨道交通组合停站方案优化

为了解决城市轨道交通运输组织中的列车停站问题,考虑列车停站与客流换乘选择之间的主从博弈关系,建立了城市轨道交通组合型停站方案的0-1双层规划数学模型。上层停站模型以运营收益最大化为目标,以车站停站下限为约束;下层乘客路径选择以总旅行耗费时间最少为目标,乘车径路连续性和可行性为约束。根据双层规划模型特点分别对决策变量、目标函数和约束条件整合处理并通过优化软件求解。通过算例分析了参数的敏感度,并证明了模型的可行性和有效性。实例应用证明了组合停站更适用于特殊空间分布的客流。     

Optimal joint replenishment,delivery and inventory management policies for perishable products

In this paper we analyze the optimal joint decisions of when, how and how much to replenish customers with products of varying ages. We discuss the main features of the problem arising in the joint replenishment and delivery of perishable products, and we model them under general assumptions. We then solve the problem by means of an exact branch-and-cut algorithm, and we test its performance on a set of randomly generated instances. Our algorithm is capable of computing optimal solutions for instances with up to 30 customers, three periods, and a maximum age of two periods for the perishable product. For the unsolved instances the optimality gap is always small, less than 1.5% on average for instances with up to 50 customers. We also implement and compare two suboptimal selling priority policies with an optimized policy: always sell the oldest available items first to avoid spoilage, and always sell the fresher items first to increase revenue.     

A heuristic algorithm for cube packing with time schedule

Packing problem has been proved to be an NP-hard problem. Many algorithms such as simulation annealing algorithm, genetic algorithm and other heuristic algorithms have been proposed to solve twodimensional and three-dimensional packing problem. To solve the cube packing problem with time schedule, this paper first introduces some concepts such as packing level, space distance and average neighbor birth order and then proposes a greedy algorithm. The algorithm tries every feasible corner greedily to calculat...     

A replenishment policy for items with price-dependent demand,time-proportional deterioration and no shortages

In this article, an order-level inventory system for deteriorating items has been developed with demand rate as a function of selling price. The demand and the deterioration rate are price dependent and time proportional, respectively. We have considered a perishable item that follows a three-parameter Weibull distribution deterioration. Shortages are not permitted in our model. The optimal solution is illustrated with a numerical example and the sensitivity analysis of parameters is carried out.     

最佳动力换档规律自学习算法的收敛性分析

针对汽车电控机械自动变速器 (AMT)最佳动力性换档规律的获取方法工作量大且耗资多,所得换档规律对其它车辆适应性差等问题,根据迭代自学习控制理论,提出了一种在线、实时寻求最佳动力性换档规律的自学习算法,并从理论上证明了该算法的收敛性,给出了收敛条件,讨论了自学习算法的快速收敛问题.分析结果表明,此法可以应用于实际AMT系统.     

单一产品复杂装配线启发式平衡排产方法

提出了一种基于Excel的单一产品复杂装配线启发式平衡排产方法。给出了基于Excel的单一产品复杂装配线启发式平衡排产方法的总体技术方案;阐述了该方法中的五个关键技术,包括将装配优先图映射为工作表,工序后接数及阶位值计算,工序排序,装配线平衡,装配线排产;通过案例分析验证了该方法的有效性。     

基于订单更改的间歇多产品厂调度在线调整研究

针对间歇化工厂产品市场变化快的特点,提出了基于订单更改的多产品厂调度在线调整模型：该模型根据生产进度对产品进行分类,并结合原调度采取相应的调整策略,得到满意的调整方案。模型基于原调度,不需增加太多变量,故在建模和实际应用中易于实现。文中将该模型用于无限中间储罐的间歇多产品厂调度在线调整实例,并通过调度调整方案对订单更改时刻的灵敏度分析找出了目标函数的影响因素。     

Efficient operation of natural gas transmission systems: A network-based heuristic for cyclic structures

In this paper we propose a heuristic solution procedure for fuel cost minimization on gas transmission systems with a cyclic network topology, that is, networks with at least one cycle containing two or more compressor station arcs. Our heuristic solution methodology is based on a two-stage iterative procedure. In a particular iteration, at a first stage, gas flow variables are fixed and optimal pressure variables are found via dynamic programming. At a second stage, pressure variables are fixed and an attempt is made to find a set of flow variables that improve the objective function by exploiting the underlying network structure. Empirical evidence supports the effectiveness of the proposed procedure outperforming the best existing approach to the best of our knowledge.     

Analysis of a multi-server queue with two priority classes and (M, N)-threshold service schedule I: non-preemptive priority

In this paper, we propose an ( M , N )-threshold non-preemptive priority service schedule for a queueing system consisting of two-parallel queues and a multi-server. The arrival process for each queue is Poisson, and the service times are exponentially distributed with different means. We derive the generating functions of the stationary joint queue-length distribution, and then obtain the mean queue length and the mean waiting time for each queue.     

Performance evaluation of a two‐echelon supply chain with stochastic demand,lost sales,and Coxian‐2 phase replenishment times

This paper deals with a two‐echelon supply chain comprising a retailer and manufacturer. The retailer faces Poisson demand and follows a (S, s) continuous review inventory policy. The manufacturer produces and ships the retailer's orders with random delay that follows the Coxian‐2 distribution. Assuming lost sales at the retailer and infinite capacity at the manufacturer, we try to explore the performance of the supply chain system. The system is modeled as a continuous‐time Markov process with discrete space. The structure of the transition matrices of these specific systems is categorized as block‐partitioned, and a computational algorithm generates the matrices for different values of system characteristics. The proposed algorithm allows the calculation of performance measures—fill rate, cycle times, average inventory (work in progress [WIP])—from the derivation of the steady‐state probabilities. Moreover, expressions for the holding costs and shortage costs are derived.     

现代家居设计中小户型怎样合理利用空间

楼市新政对楼盘户型进行了限制调整,小户型已经成为相当一部分人的居住常态,如何充分利用小小的空间,发挥小户型灵巧的优势,打造一个既温馨又有个性的小世界呢?怎样才能在小空间里做出"大文章"呢?其实,房间虽小,只要用心设计和装饰,一样能收到功能、美观两不误的效果。设计师通过巧妙的设计、合理地运用材质、多功能家具的使用以及颜色的调配等各种手段解决了小户型装修的多个难题。     

一种保持OpenFlow功能完整性的TCAM流表压缩模型

随着OpenFlow协议版本的不断更新,其在数据平面上细粒度的控制能力得到了很大提升。然而,由于表项匹配域支持的任意通配符依赖TCAM进行匹配处理,随着OpenFlow匹配域支持字段的增加,设备中的TCAM存储空间面临很大压力。为此,提出一种减小TCAM中流表存储空间的数学模型FICO(A Function-Integral TCAM-saving Compression model for flow table of OpenFlow)。FICO首先根据匹配域不同字段间的关系,将字段之间的冗余分为三种。然后基于冗余提出三种预压缩算法,分别为域间字段合并、字段映射、域内字段压缩,最终组合为更小位宽的表项被送往TCAM中进行流匹配。通过仿真表明在保持OpenFlow功能完整性的前提下,较未压缩流表,FICO可以节省60%TCAM存储空间。并且随着流表规模的增大,压缩性能保持稳定。     

空间科学实验仪器通用地面检测仪设计

针对目前空间科学实验仪器地面检测设备通用性差的问题,设计一种通用的地面检测仪.该系统具有硬件接口丰富、软件模块化、可重复配置的特点,可用于模拟星上主控平台,实现空间科学实验仪器在发射前的地面检测.结合工程实例对系统性能进行验证,结果表明,该系统能满足多数情况下的地面检测需求.     

基于改进的G-P算法的相空间嵌入维数选择

对混沌时间序列相空间重构中嵌入维数的选择进行了研究,针对饱和关联维数算法（G-P算法）存在的四点不足,提出了一种计算最佳嵌入维数的改进算法。通过对邻域半径区间的自适应选择,采用均匀变化步长的方式;对无标度区间利用基于BDS统计限定范围的快速自动判定法进行识别,实现了系统维数的自动计算;针对原算法存在的重复运算、繁杂计算问题,从算法原理和程序结构上进行了改良,大大加快求解速率。在理论分析的基础上,用新算法进行试验,仿真结果表明设计的算法对嵌入维数的选择更准确更高效。     

实现操作系统安全的几种策略

操作系统作为计算机系统中最重要的软件，其安全在整个信息安全领域内显得尤为重要。本文以操作系统需要保护的对象为线索，提供了几种操作系统的安全策略。     

Predictive pull-based control of an unmanned manufacturing cell, accounting for robot mobility

In order to remove the cell size limitation and to make cellular manufacturing systems more flexible, a manufacturing cell has been equipped with a mobile robot which moves from machine to machine, much like its human counterpart would do. To further acquire a portion of the attributes (intelligence and adaptability of the human worker) lost in robotizing the traditional manned manufacturing cell, a “limited” knowledge-based cell control algorithm is developed. This algorithm maintains standard pull control logic as its underlying basis while utilizing heuristically, knowledge of the ongoing processes and their current status. In this paper, an analysis of this ‘new’ predictive pull-based controller is presented. The simulation results from the predictive pull-based controller are evaluated and compared with the standard pull control logic, first come first serve and shortest distance. A test-bed of an unmanned manufacturing cell with a self-propelled mobile robot was used for experimental verification. Simulation and experimental results show that the degree of improvements gained in the cell performance over the standard pull control method is dependent on the robot’s mobility velocity and how much part inspection/part rejection is performed within the cell. In conclusion, the predictive pull-based algorithm is relatively simple variation of pull control which has the ability of enhancing the “near optimal” pull cell control performance.