Recency-based storage assignment and warehouse configuration for recurrent demands

Storage assignment is an important decision problem in warehouse operation management. In conventional problem settings of distribution warehouses, stock items are stored in bulk but retrieved in small quantities. Storage assignment methods typically make use of demand attribute information of order quantity, order frequency and correlation between demands. In this paper, we address a different problem in which the request for the same stock items is stochastically recurrent. The problem arises when the items are needed in production and, after production, are returned to warehouses for later reuse. Examples of such items include tooling in factory, books in library and digital objects in data warehouses. Utilizing the recurrent characteristics, a salient recency-based storage assignment policy and an associated cascaded warehouse configuration are proposed and analyzed in this paper. This paper has four parts. In the first part, a model of recurrent demand is described. In the second part, the efficiency of the recency-based policy and a traditional ID-based policy is analyzed. In the third part, a mathematical programming model for optimal configuration of cascaded warehouses is presented. Finally, a case study of hospital visits is presented. This paper concludes with recommendations on cascading and zoning the warehouse for applying the recency-based policy.     

A job assignment model for conveyor-aided picking system

Due to development and popularity of the information and automation technologies, the traditional logistics industry gradually implements the automation (e.g., sorters) or semi-automation (e.g., conveyors) techniques to support the picking operation in order to save huge labor cost of distribution centers (DCs). As for the semi-automatic picking system using the conveyor system, one of the critical issues is to appropriately assign the items to be picked to each workstation in the conveyor system in order to balance workload of each workstation and to enhance the overall resource utilization of a DC. Traditionally, the job assignment of a conveyor system is conducted by means of empirical rules or arbitrary decision of the planner and the task is usually time-consuming. As for the job assignment of the conveyor-aided picking system, this study develops a model to generate workload-balanced job assignment suggestions to the planner. In the proposed methodology, the expertise of job assignment for conveyor-aided picking system is extracted via interviews in order to derive the empirical rules for conveyor job assignment. After that, the empirical rules are quantitatively converted into empirical indices and the weights of empirical indices can be determined via the historical job assignment records. On the other hand, based on the items denoted in the picking schedule, the candidate job assignment plans are generated randomly or via the exhaustion method. Afterwards, on the basis of the derived empirical indices and corresponding weights, the optimal assignment plan can be determined. In addition to the job assignment algorithm, this study establishes a job assignment system for the conveyor-aided picking system. A real-world case is also presented to verify performance of the proposed methodology. In summary, the job assignment model proposed in this study can significantly reduce the time required for job planning for the conveyor-aided picking system and enhance applicability of the job assignment plans.     

Throughput analysis for order picking system with multiple pickers and aisle congestion considerations

Most of previous studies in picker-to-parts warehousing systems investigated only single-picker operations and are therefore adequate to evaluate order picking efficiency by travel distance as aisle congestion never takes place in such systems. In real world applications, the congestion inevitably occurs when a system has multiple pickers working together within the same region. This paper presents an approximation method based on a GI/G/1 closed queueing network by using self-correcting approximation technique algorithm to evaluate the throughput time of an order picking system with multiple pickers and aisle congestion considerations for different routing policies. The results generated by the proposed method are compared and validated via simulation model using eM-plant simulator for different sizes of warehouses. The results indicate that the approximation method appears to be sufficiently accurate for practical purposes. The sensitivity analysis of the throughput time with respect to order sizes, number of pickers and number of aisles are conducted and the performance of different item storage policies are also evaluated using the proposed approximation model.     

The effect of worker learning and forgetting on storage reassignment decisions in order picking systems

Order picking is a time-intensive and costly logistics activity as it involves a high amount of manual work. Prior research has mostly neglected the influence of human factors on the efficiency of order picking systems. This paper develops a mathematical model that investigates the impact of learning and forgetting of a heterogeneous workforce on order picking time and, consequently, on storage assignment decisions. In particular, the paper investigates when to change a storage assignment and when to keep it if learning and forgetting occur among the members of an order picking workforce. The results show that learning and forgetting should be considered in order to achieve a proper planning of storage assignment strategies.     

An advanced queueing model to analyze appointment-driven service systems

Many service systems are appointment-driven. In such systems, customers make an appointment and join an external queue (also referred to as the “waiting list”). At the appointed date, the customer arrives at the service facility and receives service. Important measures of interest include the size of the waiting list as well as the time spent in the waiting list. We develop a model to assess these performance measures. The model may be used to support strategic decisions concerning server capacity (e.g. how often should a server be online, how many customers should be served during each service session, etc.). The model is a vacation model that uses efficient algorithms and matrix analytical techniques to obtain waiting list performance measures.     

基于网格存储系统的自适应数据分配策略

在网格存储系统中通常包含各种异构的存储设备节点.基于同构系统的传统数据分配和放置策略并不能针对网格存储系统中异构存储设备的性能差异来进行数据分配,降低了网格存储系统的性能.提出一种自适应的数据分配策略(AD).通过运用基于虚拟磁盘性能的自适应分配策略和自适应的数据副本创建策略,AD能够根据存储设备节点的性能差异有效的进行数据分配.实验证明,自适应的数据分配策略能够充分发挥异构存储设备的性能,有效解决网格存储系统的数据放置不平衡问题,提高网格存储系统的利用率.     

Managing a service system with social interactions: Stability and chaos

This paper investigates the dynamic behavior of a service system in terms of the arrival rate in the steady state under the influence of social interactions. Customers are backward looking and rational when making purchasing decisions. Existing customers’ re-purchasing decisions are based on their experienced utility – a function of the average waiting time and their expected utility. Potential customers are attracted through social interactions with existing customers. It is shown that the arrival rate of the system in the steady state can exhibit stability, periodic cycles, or chaos due to the effect of social interactions and customers’ purchasing behavior. Two examples based on an M/M/1 queueing system illustrate the role of social interactions and the effect of service rates on the stability of the arrival rate in the steady state. The result highlights the dynamical complexity of a simple service system under the impact of customers’ behavioral factors, or social interactions. It suggests a new perspective to managing service operations whereby social interactions may play a critical role in the fluctuations of demand.     

Regional pole assignment for uncertain delta-operator systems

The pole assignment in a specified disk by state feedback for uncertain delta-operator systems is studied. By making use of algebra Riccati equations, a sufficient and necessary condition of pole assignment for a kind of parameter uncertain delta-operator system in a specified disk by state feedback is presented. And the design method of state feedback controller is also developed.The proposed method can unify some previous rehted results of continuous and discrete time systems into the delta framework. The efficiency of the design method is illustrated by a numerical example.     

Queueing systems with service interruptions: An approximation model

We present a single queueing model which can be used to analyse queueing systems with service interruptions. The model is based on a diffusion approximation using an instantaneous return process which reflects the particular queueing system under consideration. Applications to queueing systems with preemptive resume priority and breakdowns are given in this paper as well as numerical results showing the accuracy of the approximation.     

Question-asking strategies for Horn clause systems

An expert system applies the deduction rules in its knowledge base to a set of initial data to reach a conclusion. When the initial data are insufficient, the expert system may ask the user for additional information. This paper analyzes effectiveness and efficiency of question-asking strategies in expert systems with Horn clause knowledge bases. An effective strategy reaches a conclusion after asking as few questions as possible. An efficient strategy can be computed quickly. We prove that effective strategies are, unfortunately, not efficient. However, we present a somewhat less effective but very efficient strategy. It employs an algorithm which simultaneously performs deduction and question selection in log-linear time.Supported in part by NSF grant DMS-8513970.     

An optimal boundary for two class-based storage assignment policy in carousel system

This paper examines the effects of 2-class-based turnover assignment policy on the throughput performance of the carousel system in which a storage/retrieval machine performs pickup/discharge operations. Two alternative configurations in class boundary shape are considered. For each alternative, the expected cycle time is developed for single and dual command cycles based on the continuous analytical models. It is shown that with 2-class-based turnover assignment policy(C2) significant reductions in cycle time are obtainable over randomized storage assignment policy. The effects of the system parameters such as the skewness of the inventory distribution, the shape factor and the pickup/discharge time are studied on the optimal boundary.     

Robust pole assignment in systems subject to structured perturbations

The problem of robust pole assignment by feedback in a linear, multivariable, time-invariant system which is subject to structured perturbations is investigated. A measure of robustness, or sensitivity, of the poles to a given class of perturbations is derived, and a reliable and efficient computational algorithm is presented for constructing a feedback which assigns the prescribed poles and optimizes the robustness measure.     

A novel algorithm for performance prediction of web-based software systems

Performance metrics can be predicted with appropriate performance models and evaluation algorithms. The goal of our work is to adapt the Mean-Value Analysis evaluation algorithm to model the behavior of the thread pool. The computation time and the computational complexity of the proposed algorithm have been provided. The limit of the response time and the throughput sequences computed by the novel algorithm has been determined. It has been shown that the proposed algorithm can be applied to performance prediction of web-based software systems in ASP.NET environment. The proposed algorithm has been validated and the correctness of performance prediction with the novel algorithm has been verified with performance measurements. Error analysis has been performed to verify the correctness of performance prediction.     

Eigenvalue assignment in linear multivariable systems by output feedback

The assignment of arbitrary cloacd-loop eigenvalue spectra by output feedback is investigated in the special ease of systems for which the set of state-feedback matrices P which yield a desired closed-loop eigenvalue spectrum is finite and can be readily generated. In particular, a simple necessary and sufficient condition for the existence of an output-feedback matrix K corresponding to a prescribed state-feedback matrix P is established which also leads directly to the matrix K in cases when the condition is satisfied. The condition derived in this paper requires neither the computation of generalized inverse matrices (Munro and Vardulakis 1973), nor the transformation of state vectors (Patel 1974), nor the determination of Luenberger canonical forms (Vardulakis 1976), and indicates very clearly that an output-feedback matrix K corresponding to a prescribed state-feedback matrix P exists only in very special circumstances.     

Storage assignment problem with travel distance and blocking considerations for a picker-to-part order picking system

Order picking is a key operation in managing a warehouse efficiently. Most previous studies on picking only considered single-picker operation; however, many pickers frequently work concurrently in the same region. Since congestion may occur in such a multi-picker system, waiting time must be taken into account together with travel time and distance when evaluating the efficiency of picking operations. The picking model under investigation can be formulated as a queueing network, and a heuristic storage assignment policy that considers both the travel time and the waiting time simultaneously by minimizing the average order fulfillment time is developed in the paper. An approximation method and a simulation model using eM-plant software are presented to implement the proposed heuristic algorithm and to compare the mean travel time for different storage assignment polices as well. The results indicate that the proposed heuristic policy outperforms existing storage assignment policies in a multi-picker warehouse environment.     

Pole assignment for multi-input multi-output systems using output feedback

In this paper the problem of pole assignment using constant gain output feedback is studied for MIMO system with system order n > m + l − 1, where m and l are the number of inputs and outputs, respectively. A new procedure is presented to design a constant gain output feedback matrix which assigns (m + l − 2) poles exactly to the desired locations and shifts all the unassigned poles to suitable locations using root locus techniques.