Small Size In Order Research Articles

The supply of convenience stores: Challenges of short-distance routing within the constraints of working time regulations

Convenience stores are small shops typically located in dense urban areas. They are an important element in modern retailing considering growing urbanization. The layout of convenience stores usually differs significantly for individual stores depending on the local conditions and the types of store (e.g., grocery stores, kiosks, gas stations). Convenience stores have specific delivery requirements that differ significantly due to their variety. In this context, retailers have to cope with small order sizes and frequent deliveries that need to occur within opening hours or predetermined time windows. In addition to these requirements, working hour regulations for the drivers, i.e., the consideration of break times and tour duration restrictions, have to be respected. These regulations have so far been neglected within short-distance routing but significantly impact the planning in practice. The supply of convenience stores is thus a major challenge for retailers.This article addresses the supply of convenience stores as it takes place at a major European retailer. We develop a mathematical model that integrates existing working time regulations and actual requirements in retail practice. The resulting routing problem is solved using an adaptive large neighborhood search. We demonstrate the impact of the requirements imposed on the routing problem and corresponding delivery solutions in numerical studies. Our experiments show that ignoring break times within route planning when strict time windows are given leads to non-feasible solutions and a potential delay in deliveries of more than 18 h for a single planning week.

Analysis of Methods used to Create Digital Signals Fingerprints

Digital signals are used in many vital applications, and since the volume of this data is very large, it is necessary to represent this data with a set of values and in a small size in order to increase the speed of processing the digital signal, because the applications that use this data need a high execution speed. In this paper research a detailed study of kmeans clustering and wavelet packet tree decomposition will be introduced, Using these methods to process any type of digital signals will lead to represent the digital data by a set of small number of values, this set will be used as a fingerprint to identify the digital data. Kmeans clustering method and wavelet tree decomposition will be used to create a fingerprints for speech signals, color images and gray images, the obtained results will be analyzed to give the user a bets way to create a fingerprint for any type of digital data, which is required to build any computer system, which use the digital data as an input.

Design and Testing of a Miniature Variable Buoyancy System for Underwater Vehicles

Buoyancy-driven underwater vehicles are key tools for obtaining data from the ocean. Underwater gliders and profiling floats, equipped with sensors, provide crucial information on ocean processes and climate changes. The Variable Buoyancy System (VBS) is a key element of these vehicles, and is in many cases the most complex and highest energy-consuming subsystem. Energy consumption directly determines a vehicle’s endurance and mission duration. This paper presents the design and testing of a miniature hydraulic VBS suitable for integration into small underwater vehicles and platforms. Previous VBS are reviewed, existing principles such as hydraulics and pneumatics are described, and an overview of their strengths and weaknesses is provided. The paper explains the concept and the components of the micro-hydraulic VBS, and provides experimental results from its testing in a pressure vessel up to 1000 m equivalent depth. All the components of the system were designed to be of low weight and small size in order to be used in small underwater vehicles such as gliders and profiling floats. The efficiency of the system is characterized for different operating conditions, and provides the basis for vehicle energy system design and endurance characterizations.

Evaluating robot bin-picking performance based on Box and Blocks Test

The rise of e-commerce, which demands solutions for small order sizes, large product assortment, short delivery times, and variable order quantity has created a need for more advanced warehousing and order-picking systems. The advancements in collaborative robotics have made it possible to automate intralogistics processes, especially the order-picking systems. If the items to be order-picked are stored in small containers, called bins, the process is known as bin-picking. The processes of bin-picking are still mainly manual due to the adaptability, dexterity, and pace of human hands. However, with the emerging technologies, the gap between human and robot dexterity is getting thinner. The integrators of robotic technologies are therefore faced with the challenge of choosing an appropriate robotic system for bin-picking. There is a lack of standardized procedures, which are designed to process such decisions easier. In our research paper, we propose an improved robotic version of the Box and Blocks Test (BBT), which provides a quick evaluation of a complete robotic bin-picking system. Using our improved robot-adapted BBT protocol, we evaluate a sample robotic bin-picking system, consisting of a collaborative robot, a 3D vision system and three types of robotic grippers, comparing the bin-picking performance of each configuration.

Do Domestic Investors with the Smallest Trading Orders Use Momentum Strategies in The IDX?

This study aims to examine the use of the momentum strategy of domestic investors who trade small order sizes on IDX. The data used in this study is intraday trade transaction data from the LQ 45 Index for March, April and May 2017 obtained from The Indonesia Capital Market Institute. The method of data analysis used is the market-adjusted model approach. The results of this study indicate that domestic investors who trade in small order sizes tend to use the momentum strategy in government and non-government stock issuers. This finding implies that when IDX is in a good performance, investors should take advantage of this condition because buying stocks that have already been performing well provides a significant short-term abnormal return.

Statistical Analysis of Inventory Management Systems on Organizational Performance

The main purpose of the study was to investigate the effect of physical distribution management on organizational performance by Rutungu Distributors Ltd, Kampala (U). The study assessed the relationship between order processing and organizational performance in Rutungu Distributors Ltd in an attempt to establish the relationship between storage and organizational performance in the organization. It also sought to find out the relationship between other aspects of inventory management on organizational performance within the company. The research used a case study design approach which was correlational considering both quantitative and qualitative approaches in the data collection, presentation, and analysis. The population of the study was several categories of employees of the company. Findings from the study depicted that there is a positive significant relationship between order processing and organizational performance implying that when a customer submits an order, it is verified to ensure the necessary information is included and processed promptly. Storage and organizational performance; this means that the company can reduce damage through good materials handling. There was a positive significant relationship between inventory control and organizational performance as a result of heavy investment in inventory control practices and procedures. There was also a positive significant relationship between transportation and organizational performance showing that the company has an effective automated transportation system, observes well-coordinated fleet management practices, and also has a good vehicle maintenance policy. The study thus recommends the company to continue reducing the time it takes to get an order to a customer’s premises and to replenish its stores as it is what every company desires, but while faster fulfilment and small order sizes make customers, and store managers happy, faster fulfilment comes at a cost.

Integrated order batching and vehicle routing operations in grocery retail – A General Adaptive Large Neighborhood Search algorithm

In recent years, established and well-known grocery retailers have increasingly been investing in the business of micro stores and petrol station shops. Supplying these stores with perishable and durable goods leads to noticeable logistics challenges for the retailers. Since the total sales volumes of these shops are typically low and the respective sales areas are very limited, highly frequent deliveries of small sizes are required. These noticeably affect a number of operational planning problems. In the warehouse, the items requested have to be collected in small order sizes. In order to achieve efficient picking operations, orders are therefore combined into larger picking orders, i.e., batches. Afterwards the orders have to be delivered to the stores at high frequency. In practice, all the planning problems mentioned are heavily interconnected due to the short planning horizon.Despite the practical relevance, order batching, order picking and delivery operations have not so far been investigated as an integrative planning problem. This paper therefore presents a novel modeling and solution approach to solve practically relevant problem sizes. The combinatorial complexity of the problem requires a heuristic solution approach. We propose an extension of the well-known Adaptive Large Neighborhood Search (ALNS) metaheuristic that we call General ALNS (GALNS), and show that a GALNS approach outperforms a similar ALNS algorithm in 96.35% of the problem instances generated. Managerial insights from general problem data and a case study with a large German grocery retailer support the applicability of the modeling and solution approach suggested in retail practice.

A compressed-sensing-based compressor for ECG.

Electrocardiogram (ECG) data compression has numerous applications. The time for generating compressed samples is a vital factor when we consider ambulatory devices, with the fact that data should be sent to the physician as soon as possible. In addition, there are some wearable ECG recorders that have limited power, and may only be capable of doing simple algorithms. With the aim of increasing the speed and simplicity of the compressors, we propose a system architecture that can generate compressed ECG samples, in a linear method and with CR 75%. We used sparsity of the ECG signal and proposed a system based on compressed sensing (CS) that can compress ECG samples, almost in real-time. We applied CS in a very small size in order to accelerate the compression phase and accordingly reducing the power consumption. Also, in the recovery phase, we used the recently developed Kronecker technique to improve the quality of the recovered signal. The system designed based on full-adder/subtractor (FAS) and shift registers, without using any external processor or any training algorithm.

Incremental test data generation for database queries

Testing database applications is a complex task since it involves designing test databases with meaningful test data in order to reveal faults and, at the same time, with a small size in order to carry out the testing process in an efficient way. This paper presents an automated approach to generating test data (test relational databases and test inputs for query parameters) for a set of SQL queries, with the aim of covering test requirements as obtained from said queries. The test data generation follows an incremental approach where, in each increment, test data are generated to cover a test requirement by re-using test data previously generated for other test requirements. The test data generation for each test requirement is formulated as a constraint satisfaction problem, where constraints are derived from the test requirement, initial database states and previously generated test data. The generation process is fully automated and supports the execution on complex queries and databases. Evaluation is carried out on a real life application, and the results show that small-size generated test relational databases achieve high coverage scores for the queries under test in a short generating time.

Development of a framework for the design of autonomous vehicle storage and retrieval systems

In today’s competitive environment with increasingly faster deliveries and smaller order sizes, material handling providers are progressively developing new solutions. A more recent development in automated material-handling technology for unit load storage and retrieval is the autonomous vehicle storage and retrieval system (AVS/RS). The paper investigates the main design trade-offs for this new solution using simulation, and proposes a comprehensive design framework. Using data from a recently implemented AVS/RS, the application of the proposed framework is presented and the key design differences between the two types of AVS/RS configuration (i.e. tier-captive versus tier-to-tier) are identified.

Analytical model to estimate performances of autonomous vehicle storage and retrieval systems for product totes

In today's competitive scenario of increasingly faster deliveries and smaller order sizes, material-handling providers are progressively developing new solutions. A recent, automated material-handling technology for unit load storage and retrieval consists of an autonomous vehicle storage and retrieval system (AVS/RS). The present paper presents an analytical model to estimate the performances (the transaction cycle time and waiting times) of AVS/RS for product tote movement. The model is based on an open queuing network approach. The model effectiveness in performance estimation is validated through simulation.

Design and implementation of an embedded intrusion detection system for wireless applications

The exponential growth in wireless network faults, vulnerabilities and attacks makes the wireless local area network (WLAN) security management a challenging research area. In this study, a new embedded wireless intrusion detection system (WIDS) is designed and implemented in order to protect a multi-services wireless network. The proposed WIDS must be in small size in order to be integrated in different wireless devices, low cost in order to be placed in many places and has good performance to cover the data rate of the WLAN. All these attributes are achieved by network processor, and Ubicom network processor is used to implement the proposed WIDS. Different implementations of the proposed intrusion detection system are suggested and various searching algorithms are tested on an experimental platform. Finally, the WIDS approach is validated by experimenting with ten different types of attacks. The experimental results obtained from this work indicate that the proposed WIDS can worked efficiently at IEEE 802.11b WLAN network which provides different services to its clients with data rate ranges between 1.08 and 9.24 Mbps, and memory capacity of 250 rules.

An analytical model for A-frame system design

An A-frame system is a highly automated piece-level order-fulfillment technology. A systematic analysis is performed in this article in order to understand the design decisions of using an A-frame system in a distribution center. A math-programming-based approach to determine the amount of A-frame infrastructure investment is presented along with the assignment and allocation of Stock Keeping Units (SKUs) to the A-frame. Then throughput considerations are explicitly considered by developing analytical models for the throughput of an A-frame and heuristics to adjust the allocation and assignment of SKUs in order for the A-frame to meet a throughput constraint. The proposed heuristic approach performs well as compared to the exact solution approaches for small problems. Since the proposed methodology is capable of solving industrial-sized problems it is applied to a case study from the pharmaceutical industry. Design testing indicates that A-frame systems provide the greatest potential in labor savings when a distribution center has high item commonality, small order sizes, and high skewness levels and in throughput when many small orders have low item commonality and low skewness levels.

Development of a framework for pick-and-pass order picking system design

In today’s competitive scenario of increasingly faster deliveries and smaller order sizes, a solution that is being used more frequently is the pick-and-pass Order Picking System (OPS). The purpose of this study is to define a framework for the pick-and-pass system design, by expanding previous literature on this topic. The framework aims at minimising the overall picking costs while respecting the required service level (i.e. order throughput time), and can be easily applied to the selection stage of OPS design. The number of zones and the number of pickers per zone are among the main project data for the framework application. Analytical models are used to estimate the travel distance, and network queuing theory to analyse the mean order throughput. On the basis of the proposed framework, pick-and-pass system performance is examined as a function of two typical design conditions: order size and number of items.

Analysis of simple inventory control systems with execution errors: Economic impact under correction opportunities

Motivated by recent empirical evidence, we study the economic impact of inventory record inaccuracies that arise due to execution errors. We model a set of probable events regarding the erroneous registering of sales at each demand arrival. We define correction opportunities that can be used to (at least partially) correct inventory records. We analyze a simple inventory control model with execution errors and correction opportunities, and demonstrate that decisions that consider the existence of recording errors and the mechanisms with which they are corrected can be quite complicated and exhibit complex tradeoffs. To evaluate the economic impact of inventory record inaccuracies, we use a simulation model of a ( Q, r) inventory control system and evaluate suboptimalities in cost and customer service that arise as a result of untimely triggering of orders due to inventory record inaccuracies. We show that the economic impact of inventory record inaccuracies can be significant, particularly in systems with small order sizes and low reorder levels.

Dense habitats selecting for small body size: a comparative study on bovids

As a crucial adaptation impacting on most aspects of a species’ biology, body size is likely to be under multiple selective pressures. This study aims to determine whether the physical structure of dense habitats selects directly for small size in order to reduce resistance to movement from the vegetation and facilitate concealment (Manoeuvrability hypothesis). This is unclear because other selective forces could indirectly cause habitat to covary with body size. Focusing on bovids, I tested the explanatory power of the Manoeuvrability hypothesis in an interspecific comparative analysis controlling for phylogenetic relatedness. Bovids in dense habitats were indeed found to be reduced in size. Confirming the Food choice hypothesis, grazers, who predominantly feed on abundant food in open habitats, were found to be larger than browsers in a multivariate analysis. However, after controlling for diet there remained a residual variation in body size which correlated negatively with habitat density. No support was found for Bergmann's hypothesis as the explanation for this remaining correlation since body size did not correlate with latitude of the species’ range. Likewise, sexual selection on male body size in open habitats due to increased polygyny was an unlikely cause since body size did not correlate with sexual body size dimorphism in multivariate analysis. Rather, the finding that tail length was disproportionately shorter in closed habitats points to dense habitat structure selecting directly for compact body conformation and small size, as predicted by the Manoeuvrability hypothesis.

An association-based clustering approach to order batching considering customer demand patterns

Research on warehousing systems has gained interest since the 1980s, reflecting the fact that supply chain management has pursued a demand-driven organization with high product variety, small order sizes, and reliable short response times throughout the supply chain. This market trend has affected warehouse management and operations tremendously. Order batching in a warehouse attempts to achieve high-volume order processing operations by consolidating small orders into batches. Order batching is an essential operation of order processing in which several orders are grouped into batches. This paper describes the development of an order batching approach based on data mining and integer programming. It is valuable to discover the important associations between orders such that the occurrence of some orders in a batch will cause the occurrence of other orders in the same batch. An order-clustering model based on 0–1 integer programming can be formulated to maximize the associations between orders within each batch. From the results of several test problems, the proposed approach shows its ability to find quality solutions of order batching problems.

A comparison of picking, storage, and routing policies in manual order picking

This article examines the effect of three process decisions (picking, storage, and routing) on order picker travel, which is a major cost component of order fulfillment. The authors use a simulation model based on the operations of a distribution center that is currently picking one order at a time, storing product in a haphazard or random fashion, and using a simplistic procedure for routing pickers. Several picking, storage, and routing policies are evaluated to determine which process decision provides the greatest percent savings relative to the current baseline policies. Several sensitivity analyses are completed to examine the effect of order size, warehouse shape, location of pick-up/drop-off point, and demand distribution on performance. Results show that batching of orders yield the greatest savings particularly when smaller order sizes are common. Results also show the use of either a class-based or volume-based storage policy provides nearly the same level of savings as batching, while being less sensitive to the average order size.

Optimal pricing and ordering policies for retailers under order-size-dependent delay in payments

This paper deals with the problem of determining the retailer's optimal price and order size simultaneously under the condition of order-size-dependent delay in payments. It is assumed that the length of the credit period is a function of the retailer's order size, and also the demand rate is a function of the selling price. We formulate two types of mathematical models from which algorithms are derived based on properties of an optimal solution. A numerical example is presented to illustrate the algorithms developed. Scope and purpose Trade credit affects the conduct of business significantly for many reasons. For supplier who offers trade credit, it is an effective means of price discrimination as well as efficient method to stimulate the demand of his products. The length of credit period is considered as supplier's dominant strategy against the competitive suppliers. Among a number of factors that determine the length of the credit period in a given line of business, credit risk, the size of the account, customer type, and market competition are known to be more important. For the sake of better production and inventory control, some manufacturers in Korea prefer less frequent orders with larger order sizes to frequent orders with smaller order sizes, if the annual ordering quantities are equal. Thus they offer a longer credit period for larger amount of purchase instead of giving some discount on unit selling price. Their policies tend to make retailer's order size large enough to qualify for a certain credit period break. Based on the EOQ model, this paper analyzes the problem of the retailer who has to decide his sales price and ordering quantity simultaneously under the condition of order-size-dependent delay in payments.

Consolidation and Efficiency in the Financial Sector: A Review of the International Evidence

In response to fundamental changes in regulation and technology, the financial industry around the world is undergoing an unprecedented wave of consolidation. A growing body of empirical literature has attempted to measure the efficiency gains from M&As; however there is little sense of how the results might depend on the country, industry and time period analysed. In this paper we review critically works that cover the main sectors of the financial industry (commercial and investment banks, insurance and asset management companies) in the major industrialised countries over the last twenty years, searching for common patterns that transcend national and sectoral peculiarities. We find that consolidation in the financial sector is beneficial up to a relatively small size in order to reap economies of scale, but there is little evidence that mergers yield economies of scope or gains in managerial efficiency.