Evaluating order throughput time with variable time window batching

Given increased pressure to provide short delivery times, minimising customer order throughput time is a very important objective in warehousing operations. There are many factors that may affect the performance of an order picking system, such as layout of the warehouse, the storage strategy, the routing policy, the zoning method and the batching policy. In this study, we propose a simple travel time model and analyse the effect of order batching on the expected customer order throughput time with variable time window batching. In addition, we discussed the impact of some parameters on the batch size and the expected customer order throughput time. In the practice of Wuhan Dong Hon Logistics co. Ltd, the storage rack in the warehouse has two levels: the low storage level and the high storage level. These two levels are visited by pickers and forklifts, respectively. The classification improves the performance of order picking. In this study, we build the model based on this practice.     

拣货方式、存储策略与路径策略协同研究

对拣货方式、路径策略与存储策略进行协同研究,设计了具有代表性的策略组合。推出了不同路径策略下,实际拣货路径长度的计算公式。通过对各种策略组合仿真结果的比较分析,确定了3种策略的相对重要性:1）分批策略对减少拣货作业总时间影响最大;2）分类存储策略比随机存储策略所需的行走路径缩短很多;3）路径策略对拣货行走的时间的减少明显小于分批拣货方式和分类存储策略带来的拣货作业时间的减少。具体决策时,应优先考虑分类存储策略和分批拣货方式,在确定其已经有效的情况下再考虑路径策略,以使拣货效率达到整体最优。     

Analytical models for a new turnover-based hybrid storage policy in unit-load warehouses

This paper considers a low-level unit-load warehouse employing single-deep storage lanes and a single-command manual storage and retrieval policy. Analytical travel distance models are developed for class-based and full turnover storage policies under across-aisle, within-aisle and a newly proposed hybrid product placement schemes. Our computational studies show that the analytical models developed in this paper are very accurate as compared to simulation results and a comparative study with a real-world warehouse case. Hybrid storage policies proposed in this paper outperform all other traditional storage policies. The paper also presents insights and simple design rules to warehouse practitioners.     

Joint optimisation of order batching and picker routing in the online retailer’s warehouse in China

Order picking is the core of warehouse operations and considerable researches have been conducted on improving its efficiency. In this paper, we aim at the joint optimisation of order batching and picker routing based on a famous and typical online retailer of China, which mainly focuses on fast-moving consumer goods. An integer programming is formulated to minimise the total travelling distance involving with order batching and picker routing. In the stage of order batching, an effective batching procedure based on similarity coefficient which is measured by overlapping channels between orders is proposed. In the stage of picker routing, an improved ant colony optimisation algorithm with local search is proposed. Based on those simulated orders generated by actual transaction data, numerical experiments are conducted to verify the performance of the algorithm we proposed. Results show that the proposed joint optimisation algorithm has potential advantages under various order sizes and order structures, which implies that it is effective and efficient particularly in the online retailing of fast-moving consumer goods.     

Distributed task scheduling and human resource distribution in industrial service solution production: a simulation application

This paper provides a simulation model for scheduling service task operations and distributing related human resources in dispersed work centres. The managerial concern for the minimisation of temporal overhead costs of task operations in the face of fluctuating, short-term service demands is examined under restrictions imposed by resource availability, work hour flexibility and task-backlog fulfilment. Scheduling strategies are developed directly from the constrained reduction of temporal overheads of appointment and release operations in distributed, non-interlinked work centres. To ensure the model’s structural validity, simulated task backlogs are adjusted to the actual backlog-reducing procedures in real applications. The model provides means for setting up balanced work schedules that can greatly lower temporal overheads of appointment and release operations if workers are selected in accordance with compatible time availability and task qualifications. Direct comparisons of worker productivities in the different centres can also be made, allowing managers to locate bottleneck points of service operations when productivity falls short of desired expectations. The robustness of the model is ensured by finding significant parameter domains through Monte Carlo simulations, centred on data points collected from real-time demand functions in actual service operations.     

Tackling the storage problem through genetic algorithms

The capability of a company to implement an automated warehouse in an optimized way might be nowadays a crucial leverage in order to gain competitive advantage to satisfy the demand.The order picking is a warehouse function that needs to deal with the retrieval of articles from their storage locations.Merging several single customer orders into one,a picking order can increase efficiency of warehouse operations.The aim of this paper is to define throughout the use of ad-hoc genetic algorithm(GA) how better a warehouse can be set up.The paper deals with order batching,which has a major effect on efficiency of warehouse operations to avoid wastes of resources in terms of processes and to control possibility of unexpected costs in advance.     

Impact of required storage space on storage policy performance in a unit-load warehouse

The performance of a storage policy in a warehouse is usually evaluated on the basis of the average one-way travel distance/time needed to store/retrieve a load. Dividing the storage space into zones based on item turnover frequency can reduce the travel distance. However, for a given number of stored items, a larger number of storage zones also requires more storage space, because of reduced space sharing between the items, which increases travel time. This study considers the required space consumption by storage zoning in comparing the performance of random, full turnover-based and class-based storage policies for a unit-load warehouse operated by a forklift in single-command mode. A generalised travel distance model that considers the required space consumption is developed to compare the performance of these policies. Results show that the one-way travel distance of a random policy decreases with the increase in skewness of the demand curve. By considering the required space consumption, a class-based storage policy performs generally better than a full turnover-based policy. In addition, the optimal warehouse shape factor (ratio of warehouse width to depth) appears to decrease with the skewness of the demand curve. Warehouse managers are advised to adopt a wide-shallow warehouse layout when the item demands are approximately equal, whereas a narrow-deep layout is preferred when the demand curves are steep.     

柔性制造系统生产中的零件分批算法

根据ＦＭＳ资源、加工任务、零件工艺提出了零件分批算法，该算法在零件交货期的束下，以机床负荷平衡为目标，搜索零件集合，找出最合适的零件组合形成零件加工批。此算法为简化ＦＭＳ的动态调度和提高系统生产率创造了条件。仿真结果表明分批算法是行之有效的。     

An integrated multi-criteria Taguchi computer simulation-DEA approach for optimum maintenance policy and planning by incorporating learning effects

Modelling the maintenance activities could be complex and non-linear system which consists of different parameters. In this paper, a new approach for maintenance policy and planning problem is developed. First, maintenance activities are simulated by incorporating learning effects. Production and maintenance functions are estimated using historical data. Then, simulation is carried out for different scenarios which are combinations of periodic maintenance and different policies. Several outputs including machines and operators’ availability, reliability, efficiency and queue length are computed. Since the problem is multi-criteria, data envelopment analysis method is used to select the preferred policy. In order to show the applicability of the proposed approach, the data for a series production line is used and different scenarios with different policies are investigated. Since many scenarios are needed to be simulated, Taguchi orthogonal array design is used to reduce the number of scenarios. The proposed approach of this study would help managers to identify the preferred strategy considering and investigating various parameters and policies. This is the first study that introduces an integrated multi-criteria approach for optimum maintenance policy and planning.     

Effective bullwhip metrics for multi-echelon distribution systems under order batching policies with cyclic demand

A large number of problems in a distribution supply chain require that decisions are made in the presence of the bullwhip effect phenomenon. The impact of the order batching policies on the bullwhip effect is analysed in this paper, when cycle demand on a multi-echelon supply chain operating is considered. While investigating which bullwhip effect metrics are more adequate to measure the bullwhip effect in these type of systems, the optimal reordering plan that minimises the operation costs of the overall system is calculated. A Mixed Integer Linear Programming (MILP) model is developed that takes into account an inventory and distribution system formed by multiple warehouses and retailers with lateral transshipments. The bullwhip effect is measured through four metrics: the echelon average inventory; the echelon inventory variance ratio; the echelon average order; and the echelon order rate variance ratio. As conclusion the inventory metrics suggest that (i) using batching policy reduces instability; (ii) batching may reduce in general order variance if using larger batches and (iii) cycle demand length has no major impact in the bullwhip effect. A motivational example and a real word case study are used and tested.     

基于NSGA-Ⅱ算法的分区拣选优化

电商背景下的客户订单呈现出多品种、小批量、高频次等特点,给仓库拣选工作带来很大的挑战。为提高拣选效率,在订单完全拆分的分批策略和组合优化的行走策略下,设计了以总服务时间最小、分区工作量平衡度最优和二次分拣效率最高的多目标分区拣选模型。由于3个目标函数之间存在矛盾,设计了NSGA-II算法对多目标优化模型进行求解。通过数值实验,与传统的不拆分订单的分区拣选系统对比,发现在订单批量环境为[1,4]时,分别使总服务时间减少了43.88%,平衡度改善了84.61%,并分析了区域个数、订单总数和订单批量环境对系统效率的影响。     

Modelling on service capability maturity and resource configuration for public warehouse product service systems

The concept of service was quick to arise and has taken the world by storm in the past decade. It has gradually redefined the way warehouses are operated and has nurtured the emergence of a new kind of warehouse, namely the public warehouse (PW). Against this backdrop, a warehouse product service system (wPSS) based on the PW is established in this paper. Furthermore, in order to evaluate the service capability and optimise the resource configuration of a PW, a wPSS service capability maturity model (wPSS–SCMM) based on the analytical target cascading (ATC) algorithm is put forward. Firstly, the generation of wPSS service capability is clarified and the framework of wPSS–SCMM is proposed. After disassembling the wPSS service capability into a tree structure, its four main sub-capabilities, namely storage service capability, transportation service capability, cost control capability and time control capability, are modelled and quantised, respectively. Then the results of the four sub-capabilities are adopted in the ATC algorithm to search for the maximal service capability maturity and the optimal resource configuration solution. Finally, a numerical example of a PW with eight customers in an industrial park is analysed to demonstrate the feasibility and applicability of the proposed new approach. This research is expected to provide guidance for both investors who want to build a PW and managers who want to continuously improve an existing one.     

Ergonomic workplace design in the fast pick area

The aging society in many developed countries has made an ergonomic workplace design to an important topic among researchers and practitioners alike. We investigate the workplace design for order pickers that manually collect items from the shelves of a warehouse. Specifically, we treat the storage assignment, i.e., the placement of products in shelves of different height, and zoning, i.e., the partitioning of the storage space into areas assigned to separate pickers, in the fast pick area of a warehouse. A fast pick area unifies the most fast-moving items in a compact area, so that workers are relieved from unproductive travel, but face extraordinary ergonomic risks due to the frequent repetition of picking operations. Concerning the health of (aged) workers, it is crucial to reduce such risks. Thus, we define a combined ergonomic storage assignment and zoning problem with the objective of minimizing the maximum ergonomic burden among all workers. This problem is formalized, and two construction heuristics and a tabu search procedure are proposed. Our results show that neglecting ergonomic aspects and only focusing on picking performance leads to much higher ergonomic risks of the workforce.

     

A Stock Location Rule For A Low Level Picker-To-Part System

This paper deals with the problem of assigning warehouse space to inventory items in a low level picker-to-part system. Recognizing the importance of weights in material handling activities in warehouse, a linear programming model is developed with the objective of minimizing the workload required for order picking operations. It is proved that the stock location rule proposed in this paper generates an optimal solution for the model. Compared with the well known cube-per-order index (COI) rule, it is shown that the proposed rule is substantially better from the view point of human safety with some sacrifice of throughput.     

Enhancing the order picking process through a new storage assignment strategy in forward-reserve area

This paper reexamines the order picking process in a warehouse facing the challenges that e-commerce brings about and which are characterised by a very large number of small sized orders and returns. Implementing effective storage assignment strategies combined with efficient batching, in this context, is very fundamental to keep the warehouse’s responsiveness and order completion times up to the standards. This paper investigates a new storage assignment strategy, initially implemented by a large shoes and footwear wholesaler, to enhance the performance of the order picking process in its warehouses. The impact of this new storage assignment strategy on the performance of the order picking process is analysed via simulation. The performance of the system, measured in terms of total picking time as well as order lead time while taking congestion into account, is compared to the cases where conventional storage assignment strategies are implemented. A full factorial design is set up and the simulation output is statistically analysed. The results of this analysis are reported and thoroughly discussed. Attending to the results, the proposed strategy presents a remarkable potential to shorten total picking travel distances and order completion time and consequently customer satisfaction.     

Optimal batch ordering policies for assembly systems with guaranteed service

For a supply chain modelled as a multi-echelon inventory system, effective management of its inventory at each stock is critical to reduce inventory costs while assuring a given service level to customers. In our previous work, we used the guaranteed-service approach (GSA) to design optimal echelon batch ordering policies for continuous-review serial systems with Poisson customer demand and fixed order costs. The approach assumes that the final customer demand is bounded and each stock has a guaranteed service time in the sense that the demand of its downstream stock can always be satisfied in the service time. This paper extends this work by considering more general assembly systems. We first derive an analytical expression for the total cost of the system in the long run. The problem of finding optimal echelon batch ordering policies for the system can then be decomposed into two independent sub-problems: order size decision sub-problem and reorder point decision sub-problem. We develop efficient dynamic programming algorithms for the two sub-problems. Numerical experiments on randomly generated instances show the effectiveness of the proposed approach.     

Evaluating order picking performance trade-offs by configuring main operating strategies in a retail distributor: A Design of Experiments approach

Warehouse design has become important due to its impact on service to customers and total logistics costs. Order picking is the key activity of a warehouse and an appropriate design will directly affect its overall performance. The increasing complexity of warehouses means that the main operating strategies such as storage location assignment, batching and routing need to be considered simultaneously. A Design of Experiment approach aided by Discrete Event Simulation could help to meet these new picking design process requirements, especially when various performance measures need to be compared. Some of the trade-offs that managers must keep in mind when designing order picking systems are shown, describing a single-case study carried out at a retail distributor.     

基于Flexsim的某医药物流中心拣货流程优化研究

目的将Flexsim仿真软件应用于医药物流行业,以提高医药物流中心零货库拣货流程的运作效率。方法以某大型医药物流中心为研究对象,根据该零货库区的布局,使用Flexsim仿真软件进行建模仿真,并根据订单拣选作业流程运用Flexsim脚本语言和C语言进行了编程。分析模型运行结果,找出了瓶颈,并对拣货流程进行了优化。结果优化后的流程,提高了拣货作业的效率,缩短了拣货时间。结论采用建模仿真的方法,找出拣货流程的瓶颈问题,并进行合理优化,可以提高医药物流中心零货库的拣货效率。     

Reliability assessment of complex electromechanical systems: A network perspective

The network theory is widely applied to improve the reliability of a complex electromechanical system. In this application, system reliability assessment with network theory has been paid a great deal of attention. Because of instrument malfunctions, staff omissions, imperfect inspection strategies, and complex structures, field failure data are often subject to interval censoring, making the holistic reliability assessment becomes a difficult task. Most traditional methods assume reliability of critical components or partial reliability as system reliability, which may cause a large bias in system reliability estimation. This paper proposes a novel method to evaluate and predict the system reliability of a complex electromechanical system subject to the insufficient fault data problem from a network perspective. First, the system modeling based on network theory is developed to describe the topology of a holistic system. Second, interval‐valued intuitionistic hesitant fuzzy number is proposed in order to solve insufficient data for single component. Then, a new measure—comprehensive reliability—that can reflect the reliability of nodes in combination with functional properties and topological properties, which are formulated by failure data and network model, respectively, is constructed for system reliability assessment. Subsequently, an improved system reliability model based on percolation theory is given in terms of comprehensive reliability of nodes. Finally, to verify the effectiveness of the proposed method, a simulation and a real case study for traction system are implemented.     

订单分批算法的适用性研究

本文回顾了当前企业分拣过程中订单分批的最优算法.在人工分拣环境,在不同储位分配和仓储物品量的条件下,对订单分批的FIFS,MAA,COG,GSM,GS等五种算法进行考察.根据某国有大型企业的订单数据和计算机生成订单,采用Java编程实现各种算法,通过程序分析了不同条件下各种算法的分拣效率.实验结果表明S型分拣路线的MAA启发式算法,比其他算法优化效果更好,因此推荐采用.