Efficient algorithms for supergraph query processing on graph databases

We study the problem of processing supergraph queries on graph databases. A graph database D is a large set of graphs. A supergraph query q on D is to retrieve all the graphs in D such that q is a supergraph of them. The large number of graphs in databases and the NP-completeness of subgraph isomorphism testing make it challenging to efficiently processing supergraph queries. In this paper, a new approach to processing supergraph queries is proposed. Specifically, a method for compactly organizing graph databases is first presented. Common subgraphs of the graphs in a database are stored only once in the compact organization of the database, in order to reduce the overall cost of subgraph isomorphism testings from the stored graphs to queries during query processing. Then, an exact algorithm and an approximate algorithm for generating the significant feature set with optimal order are proposed, followed by the algorithms for indices construction on graph databases. The optimal order on the feature set is to reduce the number of subgraph isomorphism testings during query processing. Based on the compact organization of graph databases, a novel algorithm for testing subgraph isomorphisms from multiple graphs to one graph is presented. Finally, based on all the above techniques, a query processing method is proposed. Analytical and experimental results show that the proposed algorithms outperform the existing similar algorithms by one to two orders of magnitude.     

Supply Performance in Multi‐Echelon Inventory Systems with Intermediate Product Demand: A Perspective on Allocation

In this article, we study the performance of multi‐echelon inventory systems with intermediate, external product demand in one or more upper echelons. This type of problem is of general interest in inventory theory and of particular importance in supply chain systems with both end‐product demand and spare parts (subassemblies) demand. The multi‐echelon inventory system considered here is a combination of assembly and serial stages with direct demand from more than one node. The aspect of multiple sources of demands leads to interesting inventory allocation problems. The demand and capacity at each node are considered stochastic in nature. A fixed supply and manufacturing lead time is used between the stages. We develop mathematical models for these multi‐echelon systems, which describe the inventory dynamics and allow simulation of the system. A simulation‐based inventory optimization approach is developed to search for the best base‐stock levels for these systems. The gradient estimation technique of perturbation analysis is used to derive sample‐path estimators. We consider four allocation schemes: lexicographic with priority to intermediate demand, lexiographic with priority to downstream demand, predetermined proportional allocation, and proportional allocation. Based on the numerical results we find that no single allocation policy is appropriate under all conditions. Depending on the combinations of variability and utilization we identify conditions under which use of certain allocation polices across the supply chain result in lower costs. Further, we determine how selection of an inappropriate allocation policy in the presence of scarce on‐hand inventory could result in downstream nodes facing acute shortages. Consequently we provide insight on why good allocation policies work well under differing sets of operating conditions.     

Efficient Allocation of Resources for Defense of Spatially Distributed Networks Using Agent‐Based Simulation

This article presents ongoing research that focuses on efficient allocation of defense resources to minimize the damage inflicted on a spatially distributed physical network such as a pipeline, water system, or power distribution system from an attack by an active adversary, recognizing the fundamental difference between preparing for natural disasters such as hurricanes, earthquakes, or even accidental systems failures and the problem of allocating resources to defend against an opponent who is aware of, and anticipating, the defender's efforts to mitigate the threat. Our approach is to utilize a combination of integer programming and agent‐based modeling to allocate the defensive resources. We conceptualize the problem as a Stackelberg “leader follower” game where the defender first places his assets to defend key areas of the network, and the attacker then seeks to inflict the maximum damage possible within the constraints of resources and network structure. The criticality of arcs in the network is estimated by a deterministic network interdiction formulation, which then informs an evolutionary agent‐based simulation. The evolutionary agent‐based simulation is used to determine the allocation of resources for attackers and defenders that results in evolutionary stable strategies, where actions by either side alone cannot increase its share of victories. We demonstrate these techniques on an example network, comparing the evolutionary agent‐based results to a more traditional, probabilistic risk analysis (PRA) approach. Our results show that the agent‐based approach results in a greater percentage of defender victories than does the PRA‐based approach.     

An Information‐Processing Approach for Evaluating In‐Store Retail Operational Design Strategies

We develop a model to evaluate retail store operational design strategies using an information‐processing perspective of organizational design. We propose that three model constructs pertaining to in‐store shopper task uncertainty—the product mix complexity, the service production complexity, and the product mix changeover—create shopper encounter information requirements (IR). These requirements can be met using specific retail service operational design choices for managing shopper encounters, namely, designing layouts for self‐service (SS) and providing employees with task empowerment (TE). The model is then operationalized using a two‐stage approach to develop new multi‐item, measurement scales. The psychometric properties and predictive validity of the scales and model are then confirmed by using structural equation modeling with survey data from 175 merchandise retail store managers. We find that our model can be generically applied across the retail industry to understand how shopper encounter IR motivate retailer store design choices and can be used to determine whether to design stores for SS or to provide store employees with TE. We then evaluate the efficacy of the studied store design choices on customer delivery satisfaction, and offer some suggestions for future research.     

Simplified production management software for the small manufacturing firm

This paper proposes design rules in order to simplify current MRP II software systems and make them suitable for the small manufacturing firm. Simplification rules apply to production data management by reducing database complexity. This has consequences for medium-term requirements planning which is moved toward the realization of simultaneous material and capacity planning. The simplification procedure is completed by applying aggregate decision models to shop floor control which allow the introduction of a minimal transaction processing system. Object-oriented analysis concepts are used for the design of the primary production data model, which has a consistent effect on transaction data and decisional procedures throughout the whole production management software system.     

Blocking in Healthcare Operations: A New Heuristic and an Application

We consider the problem of optimal capacity allocation in a hospital setting, where patients pass through a set of units, for example intensive care and acute care (AC), or AC and post‐acute care. If the second stage is full, a patient whose service at the first stage is complete is blocked and cannot leave the first stage. We develop a new heuristic for tandem systems to efficiently evaluate the effects of such blocking on system performance and we demonstrate that this heuristic performs well when compared with exact solutions and other approaches presented in the literature. In addition, we show how our tandem heuristic can be used as a building block to model more complex multi‐stage hospital systems with arbitrary patient routing, and we derive insights and actionable capacity strategies for a real hospital system where such blocking occurs between units.     

A Design Theory Approach to Building Strategic Network‐Based Customer Service Systems*

Customer service is a key component of a firm's value proposition and a fundamental driver of differentiation and competitive advantage in nearly every industry. Moreover, the relentless coevolution of service opportunities with novel and more powerful information technologies has made this area exciting for academic researchers who can contribute to shaping the design and management of future customer service systems. We engage in interdisciplinary research—across information systems, marketing, and computer science—in order to contribute to the service design and service management literature. Grounded in the design‐science perspective, our study leverages marketing theory on the service‐dominant logic and recent findings pertaining to the evolution of customer service systems. Our theorizing culminates with the articulation of four design principles. These design principles underlie the emerging class of customer service systems that, we believe, will enable firms to better compete in an environment characterized by an increase in customer centricity and in customers' ability to self‐serve and dynamically assemble the components of solutions that fit their needs. In this environment, customers retain control over their transactional data, as well as the timing and mode of their interactions with firms, as they increasingly gravitate toward integrated complete customer solutions rather than single products or services. Guided by these design principles, we iterated through, and evaluated, two instantiations of the class of systems we propose, before outlining implications and directions for further cross‐disciplinary scholarly research.     

Agent‐Based Simulation for Human‐Induced Hazard Analysis

Terrorism could be treated as a hazard for design purposes. For instance, the terrorist hazard could be analyzed in a manner similar to the way that seismic hazard is handled. No matter how terrorism is dealt with in the design of systems, the need for predictions of the frequency and magnitude of the hazard will be required. And, if the human‐induced hazard is to be designed for in a manner analogous to natural hazards, then the predictions should be probabilistic in nature. The model described in this article is a prototype model that used agent‐based modeling (ABM) to analyze terrorist attacks. The basic approach in this article of using ABM to model human‐induced hazards has been preliminarily validated in the sense that the attack magnitudes seem to be power‐law distributed and attacks occur mostly in regions where high levels of wealth pass through, such as transit routes and markets. The model developed in this study indicates that ABM is a viable approach to modeling socioeconomic‐based infrastructure systems for engineering design to deal with human‐induced hazards.     

A Structural Equation Model of New Product Design and Development*

This research uses structural equation modeling to analyze the effects of supplier assessment, Just‐In‐Time, and quality management strategies on new product design and development. A survey of senior managers who are members of the American Production and Inventory Control Society in the United States was used to test the relationships between the constructs in the model. In general, the survey results supported the proposed structural equation model. The data showed that supplier assessment and Just‐In‐Time strategies were correlated and affected the quality management strategy used, which in turn influenced the new product design and development strategy. The data also showed that the Just‐In‐Time strategy directly influenced the new product design and development strategy.     

Interaction Between Concurrent Transactions in the Design of Distributed Databases

A distributed database system allows concurrent execution of transactions from multiple users at multiple locations. This paper presents a general scheme of including the effect of interaction between such transactions in the design process of distributed databases. This scheme allows the decision maker to choose the most appropriate design for a distributed database. The interaction effect is a consequence of concurrency control procedures and contention for system resources. Prior research has not included all components of the interaction effect in the design process. A separate module, called an interaction module, was built to measure the interaction effect using a comprehensive simulation model of a general purpose relational distributed database management system (DBMS). The interaction module can be interfaced with any distributed database design system as an add-on module so that the interaction effect can be included in the design process. A detailed example demonstrates the use of the interaction module in the decision-making process. Experiments conducted using the module show that the interaction effect can be significant and that it can affect the choice of the design. Experiments were also conducted to measure the sensitivity of design choices under changing input conditions.     

Attracting and retaining talent: exploring human resources development trends in Australia

Drawing from the resource based view of the firm (RBV) the argument developed in the paper is that in an environment characterized by increasing levels of skilled labour shortages organisations need to design employment systems that prioritize human resource development to enable competitive advantage. The literature review examines the issues associated with the attraction, retention and development of human resources, and the major contextual issues and debates underpinning skill and labour shortages. A research question is then framed to capture the HR priorities of Australian organisations. We examine responses from 1372 Australian human resources (HR) professionals who participated in an online survey of a national HR professional association and results are interpreted with respect to HR efforts to attract, develop and retain talent.

Our findings suggest that employers are addressing issues related to attraction - recruitment and selection. However, in critical HR development areas associated with retention such as training, job design, skill development, careers management and team building, results indicate a lower level of resource allocation. We conclude that this lack of resource allocation is of concern for Australian organisations that are struggling to compete both domestically and internationally for skilled workers.     

基于模糊权重的多目标订单分配模型

随着竞争的日益加剧,采购成了影响企业生存和发展的关键因素。在这种情况下,正确的订单分配是成功实行采购的关键。实际上,影响订单分配的许多信息并不是确定的已知条件,例如目标、约束条件和影响权重等。本文通过考虑上述信息的不确定性和模糊性,构建一个包含模糊目标、模糊权重和随机约束的订单分配模型。然后,利用数值算例证明了模型的可解性。最后,指出了未来可能的几个研究方向。     

Survey of resource allocation methods for distributed manufacturing systems

Distributed manufacturing systems are more flexible in their arrangement and use of their resources. This permits a more dynamic and opportunistic allocation of manufacturing resources to work elements than is possible with today's centralized allocation systems. However, unlike solving the problem from a single solver view, there is no absolute control or tight coordination over how and when to decompose the problem, when to undertake a solution or the procedure for verifying consistency. Such activities will largely be left to the distributed entities to decide either individually or jointly. As a consequence the resulting allocations may suffer and induce myopic behaviour lacking in stability and regularity in the performance of the total system. Thus, the issues connected with solving the problem often move beyond the pure algorithmic focus of computation to include how the problem is decomposed, how or to whom it is assigned, and the organization for solving the subproblems, strategies used for resolving conflicts, the manner in which communication is conducted, etc. These issues, in fact, highlight the holistic nature of the solution and are used here as parameters to compare and contrast the approaches reported in the literature.     

A Data‐Driven Inventory Control Policy for Cash Logistics Operations: An Exploratory Case Study Application at a Financial Institution

A number of market changes are impacting the way financial institutions are managing their automated teller machines (ATMs). We propose a new class of adaptive data‐driven policies for a stochastic inventory control problem faced by a large financial institution that manages cash at several ATMs. Senior management were concerned that their current cash supply system to manage ATMs was inefficient and outdated, and suspected that using improved cash management could reduce overall system cost. Our task was to provide a robust procedure to tackle the ATM's cash deployment strategies. Current industry practice uses a periodic review system with infrequent parameter updates for cash management based on the assumption that demand is normally distributed during the review period. This assumption did not hold during our investigation, warranting a new and robust analysis. Moreover, we discovered that forecast errors are often not normally distributed and that these error distributions change dramatically over time. Our approach finds the optimal time series forecaster and the best‐fitting weekly forecast error distribution. The guaranteed optimal target cash inventory level and time between orders could only be obtained through an optimization module that was embedded in a simulation routine that we built for the institution. We employed an exploratory case study methodology to collect cash withdrawal data at 21 ATMs owned and operated by the financial institution. Our new approach shows a 4.6% overall cost reduction. This reflects an annual cost savings of over $250,000 for the 2,500 ATM units that are operated by the bank.     

A Risk-sharing Approach to Transfer Pricing and Incentive Compensation Problems under Exchange Rate Uncertainty*

This study examines the transfer pricing and incentive compensation problems in a multinational enterprise facing currency risk. It is shown that, in the presence of diverse risk preferences among managers, the Hirshleifer (1956) transfer pricing rule results in inefficient resource allocation decisions by division managers. Following the approach developed by Kanodia (1979), two transfer pricing and compensation systems are proposed. The proposed systems enable central management to achieve efficient resource allocation and partial or global risk sharing. It is also argued that the proposed plans can be implemented in conjunction with existing transfer pricing systems that primarily serve tax and tariff concerns.     

A solution framework for the multi-mode resource-constrained cross-dock scheduling problem

In this paper we propose a framework for shift-level container scheduling and resource allocation decisions at a cross-dock facility. The Multi-Mode Resource-Constrained Cross-Dock Scheduling Problem (MRCDSP) approach minimizes material flow and schedules inbound and outbound containers to dock-doors such that the total processing time is minimized subject to the resource constraints at the cross-dock. While container scheduling and resource allocation problems at cross-dock facilities have been studied previously in isolation, our work is the first to consider a complete view of cross-dock operations providing optimal container to dock-door allocation, and a makespan minimizing schedule of containers to the cross-dock. We present a comprehensive framework that includes identification of container clusters to reduce the problem size, a container-to-dock-door assignment algorithm, and a container clusters scheduling model that is solvable for practically sized problems. In a comparative numeric study based on data simulating a cross-dock facility, our approach is shown to outperform current practice, reducing the average time required for processing a set of containers by 37% and reducing the weighted-distance material traveled within the cross-dock by 45%.     

基于虚拟数据库的决策支持系统

在网络技术快速发展的知识经济时代,企业决策者特别需要信息和知识的支持。虚拟数据库技术能够快速收集、组织和集成来自不同数据源的数据,并以统一的关系数据库的形式提供给决策者和上层应用程序,便于数据挖掘和在线分析处理,提高系统决策支持的能力。在此基础上,本文提出了一种新的易于实现的决策支持系统体系结构。     

大型建筑工程项目资源配置模型及策略研究——基于系统动力学的建模和仿真

大型建筑工程项目多类型资源的有效配置,是现阶段项目管理理论与工程管理实践面临的关键问题,特别是在考虑工艺顺序和间歇时间的工作可操作性特点,以及多资源之间反馈影响的情况下。通过整合挣值法和系统动力学理论,在分析资源可用性和工作可操作性之间因果关系的基础上,本文构建了大型建筑工程项目多资源配置的系统动力学模型。以上海市重大工程投资统计数据作为模型参数依据,模型的仿真结果表明:建筑工程项目不同类型资源其配置重要性与系统影响性存在显著差异,在制定资源配置策略时应同时考虑项目运作方式的特征与多资源之间的匹配,资源不匹配则容易导致资源配置系统失去稳态或策略失效。这为进一步研究项目管理中多资源配置提供了理论参考和实践支持。     

A new approach for understanding dominant design: The case of the ink-jet printer

We study dominant design strategies concerning the allocation of technological resources for ink-jet printers. We find that the dominant design for each firm can be quantitatively represented by the number of ink-jet patents in nine categories of a matrix that distinguishes patents according to method of implementation and type of module. Further, we find that annual firm ink-jet revenue from 1990 through 2000 is positively correlated with a balanced dispersion of patents across the nine categories. Results suggest that higher revenues will accrue to firms in integrated industries when resources are balanced among important sub-technologies in the dominant design.     

PERFORMANCE ANALYSIS OF AN ASSEMBLY STATION WITH INPUT FROM MULTIPLE FABRICATION LINES

We develop analytical models for performance evaluation of Fabrication/Assembly (F/A) systems. We consider an F/A system that consists of an assembly station with input from K fabrication lines. Each fabrication line consists of one or more fabrication stations. The system is closed with a fixed number of items circulating between each fabrication line and the assembly station. We present algorithms to estimate the throughput and mean queue lengths of such systems with exponential processing times. We then extend our approach to analyze F/A systems with general processing time distributions. Numerical comparisons with simulations demonstrate the accuracy of our approach.