Developing a step-by-step effectiveness assessment model for customer-oriented service organizations

Effectiveness involves more than simple efficiency, which is limited to the production process assessment of peer operational units. Effectiveness incorporates variables that are both controllable (i.e. efficiency) and non-controllable (i.e. perceived quality) by the operational units. It is a fundamental driver for the success of either a for-profit or a non-for-profit unit in a competitive environment that is customer/citizen- and goal-oriented. Additionally, with respect to the short-run production constraints, i.e. the resources available and controllable by the operational units, and the legal status, we go beyond the traditional effectiveness assessment techniques by developing a Modified or “rational” Quality-driven-Efficiency-adjusted Data Envelopment Analysis (MQE-DEA) model. This particular model provides in the short run a feasible effectiveness attainment path for every disqualified unit in order to meet high-perceived quality and high-efficiency standards. By applying the MQE-DEA model a new production equilibrium is determined, which is different from the equilibrium suggested by the mainstream microeconomic theory, in that it takes into account not only the need for operational efficiency but also the customer-driven market dynamics.     

Operational risk modelling and organizational learning in structured finance operations: a Bayesian network approach

This paper describes the development of a tool, based on a Bayesian network model, that provides posteriori predictions of operational risk events, aggregate operational loss distributions, and Operational Value-at-Risk, for a structured finance operations unit located within one of Australia's major banks. The Bayesian network, based on a previously developed causal framework, has been designed to model the smaller and more frequent, attritional operational loss events. Given the limited availability of risk factor event information and operational loss data, we rely on the elicitation of subjective probabilities, sourced from domain experts. Parameter sensitivity analysis is performed to validate and check the model's robustness against the beliefs of risk management and operational staff. To ensure that the domain's evolving risk profile is captured through time, a formal approach to organizational learning is investigated that employs the automatic parameter adaption features of the Bayesian network model. A hypothetical case study is then described to demonstrate model adaption and the application of the tool to operational loss forecasting by a business unit risk manager.     

Security and coordination in a clandestine organization

We develop a model of an underground organization. The model is designed to highlight the tradeoff between the operational capacity and operational security of clandestine groups. The underground in this paper is defined by a collection of individual cells that are united by a network of internal communications. The attributes of this network, we show, have important implications for the vitality of an underground group in the face of regime efforts to identify and target its component cells. We examine the implications of various network designs for group performance in the short run, and the implications the group's short run performance will have for its operational prospects in the long run. In the final section of the paper, we discuss the conditions under which a conflict between a regime and an underground organization will reach three alternative equilibria. The results of this paper will be useful to those interested in both the design and dismemberment of clandestine organizations.     

Column generation based heuristic for tactical planning in multi-period vehicle routing

The periodic vehicle routing problem (PVRP) consists in establishing a planning of visits to clients over a given time horizon so as to satisfy some service level while optimizing the routes used in each time period. The tactical planning model considered here restricts its attention to scheduling visits and assigning them to vehicles while leaving sequencing decisions for an underlying operational model. The objective is twofold: to optimize regional compactness of the routes in a desire to specialize routes to restricted geographical area and to balance the workload evenly between vehicles. Approximate solutions are constructed using a truncated column generation procedure followed by a rounding heuristic. This mathematical programming based procedure can deal with problems with 50–80 customers over five working days which is the range of size of most PVRP instances treated in the literature with meta-heuristics. The paper highlights the importance of alternative optimization criteria not accounted for in standard operational models and provides insights on the implementation of a column generation based rounding heuristic.     

服务型制造网络资源整合决策优化模型

服务型制造是制造业发展的新模式,服务型制造的顺利开展依赖于对服务型制造网络中各种资源的整合及优化.分析服务型制造网络的运作特征, 在此基础上将决定网络和个体运作水平的硬环境因素和软环境因素作为服务型制造网络资源整合的主导因素,提出基于主导因素评判的资源整合决策模式,构建出优化整合决策的数学模型,搭建了改进的蚁群寻优算法来求解整合决策的优化过程,最后借助算例仿真验证算法的有效性与可行性。     

Measuring overall efficiency and effectiveness using DEA

This paper presents a framework where data envelopment analysis (DEA) is used to measure overall efficiency and show how to apply this framework to assess effectiveness for more general behavioral goals. The relationships between various cone-ratio DEA models and models to measure overall efficiency are clarified. Specifically it is shown that as multiplier cones tighten, the cone-ratio DEA models converge to measures of overall efficiency. Furthermore, it is argued that multiplier cone and cone-ratio model selection must be consistent with the behavioral goals assigned or assumed for purposes of analysis. Consistent with this reasoning, two new models are introduced to measure effectiveness when value measures are represented by separable or linked cones, where the latter can be used to analyze profit-maximizing effectiveness.     

A Bayesian network structure for operational risk modelling in structured finance operations

This paper is concerned with the design of a Bayesian network structure that is suitable for operational risk modelling. The model's structure is designed specifically from the perspective of a business unit operational risk manager whose role is to measure, record, predict, communicate, analyse and control operational risk within their unit. The problem domain modelled is a functioning structured finance operations unit within a major Australian bank. The network model design incorporates a number of existing human factor frameworks to account for human error and operational risk events within the domain. The design also supports a modular structure, allowing for the inclusion of many operational loss event types, making it adaptable to different operational risk environments.     

Analysing emergency medical service ambulance deployment on a Brazilian highway using the hypercube model

In this study we analyse the ambulance deployment of an emergency medical system on a Brazilian highway connecting the cities of São Paulo and Rio de Janeiro. Our focus is on the mean response time of the system to an emergency call, viewed as an important component of the user service. To evaluate the system performance we applied the hypercube model, a well-known tool for planning server-to-customer systems, which is based on spatially distributed queuing theory. The results showed that the model can be effective in supporting design and operational decisions, in particular to reduce the workload unbalancing among the ambulances.     

A web-based workforce management system for Sainsburys Supermarkets Ltd

Labour scheduling plays an important and critical role in Sainsburys day to day operations and profitability. The integrated workforce management solution for Sainsburys is an intelligent solution for the operational deployment of human resources, integrated business forecasting, generation and calculation of workload and staff scheduling. The workforce management technology has provided Sainsburys with a fully web-based and centralised system that produces optimised schedules for all employees satisfying the forecasted demand of work with granularity of fifteen minutes. The system is configured to respect all operational and business requirements as well as employee contractual constraints. This paper introduces the workforce management solution system designed, developed and implemented for Sainsburys. We concentrate on two modelling structures, namely the work pattern model and optimisation model, and briefly discuss the optimisation process.     

COMPASS—the verification and validation of an operational analysis model for use in the prediction of Nimrod MRA4 operational effectiveness

Comprehensive Maritime Patrol Aircraft Systems Simulation (COMPASS) is a mathematical model of the Nimrod MRA4 weapon system that is being developed to enable the prediction of operational effectiveness. COMPASS will be used throughout the Nimrod MRA4's development life cycle to conduct tactics development and weapon system performance evaluation. Following Nimrod MRA4's entry into service, the COMPASS model may be used by the customer, the Ministry of Defence (MoD) Defence Procurement Agency (DPA), to assess operational effectiveness of potential system upgrades and to evaluate the effect of changes to the threat or operating environment. BAE SYSTEMS is developing tactical scenarios to test operational performance. The operational requirement is decomposed, at the highest practicable system level, into metrics that can be measured easily under test or trials conditions. Having quantified a system's capabilities in these lower level metrics, COMPASS can be modified to reflect them accurately. COMPASS uses these tactical scenarios to simulate the Nimrod MRA4 undertaking a number of Anti Submarine Warfare (ASW) and Anti Surface Unit Warfare (ASuW) activities. This paper describes the philosophy and process being applied to the development of a fully verified and validated COMPASS mathematical model. It also details the approach to using COMPASS to determine Nimrod MRA4 operational effectiveness through the construction of tactical scenarios.     

模糊综合评判地空导弹武器系统作战效能的一种方法

为科学评估地空导弹武器系统的作战效能,对地空导弹武器系统进行了全面分析,建立了地空导弹武器系统作战效能综合评价的指标体系.并利用模糊数学方法,确立了该系统的综合评价模型,从而为地空导弹武器系统的总体作战效能的综合评价提供了一种方法,具有一定的参考价值.     

Workload distributions in ASIP queueing networks

Queueing Systems - The workload of a generalized n-site asymmetric simple inclusion process (ASIP) is investigated. Three models are analyzed. The first model is a serial network for which the...     

Continuous polling models and application to ferry assisted WLAN

In this paper we focus on a class of polling systems encountered while modeling the ferry based wireless local area network (FWLAN). A moving ferry, while walking in a predetermined cyclic path, communicates with the static nodes (or users) of the network via a wireless link. The ferry is assumed to stop and communicate with a node that has a packet to send or to receive, when it is closest to that node. The location distribution of the node to which or from which a packet arrives is assumed to have a support of positive Lebesgue measure. These features imply that polling models with finite number of queues cannot be used to model the system. We study in this paper the continuous polling systems with service disciplines that model the use of the FWLAN (and that are more complex than the classical exhaustive or gated services). Our approach is based on discretization of the continuous polling model. We propose a special way of discretizing the continuous system such that: (1)?the known Pseudo conservation laws can be applied to obtain the stationary expected workload of the discrete systems; (2)?the limit, of these ??discretized' expected workloads, equals the stationary expected workload of the continuous system. Our results rely heavily on fixed point analysis of infinite dimensional operators.     

The sector design and assignment problem for snow disposal operations

Winter road maintenance operations involve a host of decision-making problems at the strategic, tactical, operational, and real-time levels. Those operations include spreading of chemicals and abrasives, snow plowing, loading snow into trucks, and hauling snow to disposal sites. In this paper, we present a model and two heuristic solution approaches based on mathematical optimization for the problem of partitioning a road network into sectors and allocating sectors to snow disposal sites for snow disposal operations. Given a road network and a set of planned disposal sites, the problem is to determine a set of non-overlapping subnetworks, called sectors, according to several criteria related to the operational effectiveness and the geographical layout, and to assign each sector to a single snow disposal site so as to respect the capacities of the disposal sites, while minimizing relevant variable and fixed costs. Our approach uses single street segments as the units of analysis and we consider sector contiguity, sector balance and sector shape constraints, hourly and annual disposal site capacities, as well as single assignment requirements. The resulting model is based on a multi-commodity network flow structure to impose the contiguity constraints in a linear form. The two solution approaches were tested on data from the city of Montreal in Canada.     

国有企业的供应商优选决策研究——兼顾政策性负担与经济性目标

国有企业对政策性负担的承担常常以其经济效益的损失为代价,保持政策性负担和经济性目标的平衡,对国企的可持续发展而言意义重大。国有企业的供应商选择是影响其政策性负担与经济性目标平衡发展的关键运营策略之一。其中,供应链成员的性质及其在改善就业、养老和社会稳定等方面的作用是国有企业所承担政策性负担的重要影响因素;供应链成员的能力则对国有企业的经济性指标有重大影响。首先,将国有企业所承担的政策性负担转化为一系列非经济性目标,并对其进行量化分析。在此基础上,构建了以非经济性指标和经济性指标为优化目标的供应商优选模型,并搭建了求解算法。最后,以算例验证了模型和算法的有效性与可行性。结果显示,所构建的供应商优选模型能够有效地使国有企业的经济性目标及其所承担的政策性负担都得到优化。     

Operational knowledge management: identification of knowledge objects,operation methods,and goals and means for the support function

Though much has been written about knowledge management, this field has not been described extensively from an operational management perspective. Consequently, knowledge management seems difficult to implement at the operational levels of the organisations. To solve this problem, the abstract notion of knowledge is translated in operational knowledge objects. These objects are the input and output of two operation methods: (1) transformation or learning; and (2) knowledge logistics. The article describes several activities of these operation methods, and gives a classification of operational goals and means for the operations support function. The author concludes with mentioning challenges for the field of operational knowledge management.     

Fluid approximation for generalized Jackson network with vacations

Using a bounding technique, we prove that the fluid model of generalized Jackson network (GJN) with vacations is the same as a GJN without vacations, which means that vacation mechanism does not affect the dynamic performance of GJN under fluid approximation. Furthermore, in order to present the impact of vacation on the performance of GJN, we show that exponential rate of convergence for fluid approximation only holds for large N, which is different from a GJN without vacations. The results on fluid approximation and convergence rate are embodied by the queue length, workload, and busy time processes.     

Stochastic actor‐oriented models for network change

A class of models is proposed for longitudinal network data. These models are along the lines of methodological individualism: actors use heuristics to try to achieve their individual goals, subject to constraints. The current network structure is among these constraints. The models are continuous time Markov chain models that can be implemented as simulation models. They incorporate random change in addition to the purposeful change that follows from the actors’ pursuit of their goals, and include parameters that must be estimated from observed data. Statistical methods are proposed for estimating and testing these models. These methods can also be used for parameter estimation for other simulation models. The statistical procedures are based on the method of moments, and use computer simulation to estimate the theoretical moments. The Robbins‐Monro process is used to deal with the stochastic nature of the estimated theoretical moments. An example is given for Newcomb's fraternity data, using a model that expresses reciprocity and balance.     

Strategic design of competing supply chain networks for inelastic demand

A model for designing the network of a new entrant supply chain under inelastic demand and in the presence of pre-existing competing chains is proposed. These supply chains provide an identical product for a market area. The model considers the location of distribution centres and retail outlets on a discrete set of potential locations. The assumptions of the model are: (1) static competition between the new and pre-existing chains and (2) a probabilistic customer behaviour based on an attraction function depending on both the location and the quality of the retailers. This model also incorporates the impact of the facilities’ location decisions on the operational inventory and shipment decisions. The resulting model is formulated as a mixed integer non-linear programme (MINLP). To solve the MINLP it is transformed to a linear one. We illustrate the model, discuss the results of a real-world case, and investigate the effectiveness of the proposed algorithm using randomly generated examples.     

Operational and financial effectiveness of e-collaboration tools in supply chain integration

This paper develops a comprehensive model of supply chain integration and uses it to analyze and assess the operational and financial effectiveness of different e-collaboration tools at various levels of supply chain integration. This model is also used to evaluate the importance of the sequence in which e-collaboration tools are adopted in supply chain integration. Computational results from a validated system dynamics simulation model with different implementation sequences of e-collaboration tools and different financial scenarios show that local financial constraints can also severely impact operational and financial performance of the entire supply chain.