Multiechelon (R,S) Inventory Model*

Most studies in multiechelon inventory systems have concentrated on understanding the specific aspects of a system's behavior. The problem of optimal policy computation has largely been ignored. In this paper, we investigate a two-echelon inventory system experiencing stochastic demand and a pull system of inventory allocation. Both echelons use an order-up-to-level type control policy. A mathematical model is developed to determine the optimal order level at all echelons and validated through simulation. Two simple algorithms to locate the optimum solution are presented. The use of graphical tools in optimal policy calculation is also discussed.     

Urban and regional planning—A systems view

The most interesting developments in the search for new planning procedures are in the areas of ecology, as an eco system with the matrix structure of environmental impact analysis, and Ekistics, the science of human settlement. The grid system developed in this approach combined with the environmental impact analysis model, provides a complete systems approach. The problem is to relate this to systems dynamics and to integrate this approach with the concept of society as a dynamic social system. The literature review highlights key works which lead to or use the systems approach. By attempting to identify a systems approach many planning techniques and concepts are not included. However, if one adopts this approach it is possible to test the use of any technique within a recognized framework and not on the piecemeal basis which is used at present.     

物流配送车辆路径规划模型的知识表示研究

针对物流配送车辆路径规划的实时动态建模问题,以解决模型的目标函数和约束等符号化知识的知识表示及基于知识的求解机制为突破口,提出了以七元组M=(B,O,C,I,P,E,D)表示车辆路径规划模型的知识表示方法--BOCIPED表示法;并以沈阳昌达集团餐饮配送公司为应用背景,设计建立了相应的车辆路径规划问题的建模与求解系统,通过系统的实际应用,验证了系统中BOCIPED表示方法的可行性与有效性.本研究为车辆路径规划这一难题提供由计算机自动生成模型并求解的新方法,有利于建立高智能的物流配送实时调度系统.     

Order Dispatching and Labor Assignment in Cellular Manufacturing Systems

Although order and labor dispatching in the job shop manufacturing setting have been investigated extensively over the last three decades, its representation of actual processes found in practice today is limited due to the move to cellular manufacturing (CM). Manufacturing cells have become an important approach to batch manufacturing in the last two decades, and their layout structure provides a dominant flow structure for the part routings. The flow shop nature of manufacturing cells adds a simplifying structure to the problem of planning worker assignments and order releases, which makes it more amenable to the use of optimization techniques. In this paper we exploit this characteristic and present two mathematical modeling approaches for making order dispatching and labor assignment/reassignment decisions in two different CM settings. The two formulations are evaluated in a dynamic simulation setting and compared to a heuristic procedure using tardiness as the primary performance measure. The formulations are superior to the heuristic approach and can be incorporated into detail scheduling systems that are being implemented by corporations employing enterprise resource planning (ERP) systems today.     

A Multiple Objective Embedded Network Model for Human Resource Planning and an Implementation of the Tchebycheff Method

A multiple objective embedded network model is proposed to model a variety of human resource planning problems including executive succession planning, compensation planning, training program design, diversity management and human systems design. The Tchebycheff Method, an interactive multiple objective programming solution procedure developed by Steuer and Choo [32], is implemented using NETSIDE, a computer routine for solving network problems with side constraints developed by Kennington and Whisman [17]. This paper demonstrates how the network structure common to many types of human resource planning problems can be exploited to improve solution efficiency, and how our approach extends the use of network models in human resource planning by including multiple objectives and extranetwork constraints. An illustrative example demonstrating the modeling and solution approach is presented, and the potential applications of these approaches in two specific areas of human resource planning are discussed.     

MANAGERIAL USE OF DYNAMIC STRUCTURAL MODELS*

Dynamic structural models were introduced as early as 1958 as “Industrial Dynamics, but there has been little managerial use and little response in the academic world. Yet, the basic modeling methods provide an important mode for examining the broad interacting effects of large systems. More recent work appears to make structural and dynamic models understandable and accessible to individuals not trained in the decision sciences. The nature of the modeling methods is such that managers and policy makers in public systems can be involved directly in the model building process. The authors hope that this survey paper may help rekindle interest.     

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.     

DECENTRALIZED MULTIECHELON INVENTORY CONTROL

This paper considers a model for decentralized control of an inventory system consisting of 1 central warehouse and a number of retailers. The cost structure includes holding costs at both echelons and shortage costs proportional to the time until delivery at the retailers. We analyze a procedure for coordinated but still decentralized control of the system. The procedure is based on a simple approximation, in which the stochastic lead times perceived by the retailers are replaced by their correct averages. The approximation enables us to decompose the considered multiechelon inventory problem into a number of single echelon problems, 1 for each installation. The information about how a certain decision at the warehouse affects the retailers is conveyed through the marginal cost increase with respect to a change of the expected lead time. This information about the retailer costs is used as a shortage cost at the warehouse. We show that a coordination procedure based on this information can be used for finding near-optimal reorder points for the system and provide bounds for the approximation errors.     

Characterizing performance in socio-technical systems: A modeling framework in the domain of nuclear power

In modeling complex socio-technical systems, the critical nature of many interactions between human and automation are often unrecognized until the system experiences catastrophic consequences. One reason for this is that the systems are generally very robust and serious problems are rare. Another reason is the difficulty in modeling the variety of interactions in a manner compatible with analytical and/or computational models of the technological components of the system. Organizational issues and extraneous influences add to these modeling difficulties. We have developed a modeling framework that integrates certain ideas from social networks, graph theory, and simulation, all tied together using heuristics that reflect deep domain knowledge. This framework forms the basis for a computational implementation, portions of which have been implemented. Details of the model and the rationale for the model structure are described in this paper.     

随机期限结构与国债定价模型

假设债价扩散函数v(t,T)为时间t的二次函数,是利用风险中性方法建立随机期限结构模型的关键;而随机期限结构模型又是建立债券定价模型的基础。本文不但介绍了有关的理论模型,而且利用我国国债市场的价格数据进行实证研究,建立了具体的瞬态年利率随机期限和国债961的定价模型。     

Anreizsysteme und Unternehmensethik

The article analyses the structuring of incentive systems from a business ethics point of view. The focus is on examining the impact of different types of social preferences on wage compensation. Besides the structuring of incentive systems, especially the effects of different types of social preferences on firm profits are analyzed. The paper systematizes important determinants for the impact of social preferences on the structure of the incentive system as well as firm profitability and provides an overview over the literature employing formal models based on a possibly general modeling approach.     

MORM—A Petri Net Based Model for Assessing OH&S Risks in Industrial Processes: Modeling Qualitative Aspects

Because of the increase in workplace automation and the diversification of industrial processes, workplaces have become more and more complex. The classical approaches used to address workplace hazard concerns, such as checklists or sequence models, are, therefore, of limited use in such complex systems. Moreover, because of the multifaceted nature of workplaces, the use of single-oriented methods, such as AEA (man oriented), FMEA (system oriented), or HAZOP (process oriented), is not satisfactory. The use of a dynamic modeling approach in order to allow multiple-oriented analyses may constitute an alternative to overcome this limitation. The qualitative modeling aspects of the MORM (man-machine occupational risk modeling) model are discussed in this article. The model, realized on an object-oriented Petri net tool (CO-OPN), has been developed to simulate and analyze industrial processes in an OH&S perspective. The industrial process is modeled as a set of interconnected subnets (state spaces), which describe its constitutive machines. Process-related factors are introduced, in an explicit way, through machine interconnections and flow properties. While man-machine interactions are modeled as triggering events for the state spaces of the machines, the CREAM cognitive behavior model is used in order to establish the relevant triggering events. In the CO-OPN formalism, the model is expressed as a set of interconnected CO-OPN objects defined over data types expressing the measure attached to the flow of entities transiting through the machines. Constraints on the measures assigned to these entities are used to determine the state changes in each machine. Interconnecting machines implies the composition of such flow and consequently the interconnection of the measure constraints. This is reflected by the construction of constraint enrichment hierarchies, which can be used for simulation and analysis optimization in a clear mathematical framework. The use of Petri nets to perform multiple-oriented analysis opens perspectives in the field of industrial risk management. It may significantly reduce the duration of the assessment process. But, most of all, it opens perspectives in the field of risk comparisons and integrated risk management. Moreover, because of the generic nature of the model and tool used, the same concepts and patterns may be used to model a wide range of systems and application fields.     

An Arborescent Network Formulation and Dual Ascent Based Procedure for the Two-Stage Multi-Item Dynamic Demand Lotsize Problem

Traditional approaches for modeling and solving dynamic demand lotsize problems are based on Zangwill's single-source network and dynamic programming algorithms. In this paper, we propose an arborescent fixed-charge network (ARBNET) programming model and dual ascent based branch-and-bound procedure for the two-stage multi-item dynamic demand lotsize problem. Computational results show that the new approach is significantly more efficient than earlier solution strategies. The largest set of problems that could be solved using dynamic programming contained 4 end items and 12 time periods, and required 475.38 CPU seconds per problem. The dual ascent algorithms averaged .06 CPU seconds for this problem set, and problems with 30 end items and 24 time periods were solved in 85.65 CPU seconds. Similar results verify the superiority of the new approach for handling backlogged demand. An additional advantage of the algorithm is the availability of a feasible solution, with a known worst-case optimality gap, throughout the problem-solving process.     

When should organizational change be implemented? The moderating effect of environmental dynamism between dynamic capabilities and new venture performance

The purpose of this study is to explore the moderating effect of environmental dynamism on the relationship between dynamic capabilities and new venture performance using the rapidly changing environment in China as a case. Using a sample of 115 firm observations, we applied the partial least squares structural equation modeling approach to model these relationships and found that opportunity-sensing capability and reconfiguration capability have significant impacts on new venture performance. Additionally, each of these capabilities has a stronger impact on new venture performance at higher levels of environmental dynamism. We conclude that dynamic capabilities are more effective in implementing organizational change at high degrees of environmental dynamism.     

Managing Production and Distribution for Supply Chains in the Processed Food Industry

We develop and evaluate a modeling approach for making periodic review production and distribution decisions for a supply chain in the processed food industry. The supply chain faces several factors, including multiple products, multiple warehouses, production constraints, high transportation costs, and limited storage at the production facility. This problem is motivated by the supply chain structure at Amy's Kitchen, one of the leading producers of natural and organic foods in the United States. We develop an enhanced myopic two‐stage approach for this problem. The first stage determines the production plan and uses a heuristic, and the second stage determines the warehouse allocation plan and uses a non‐linear optimization model. This two‐stage approach is repeated every period and incorporates look‐ahead features to improve its performance in future periods. We validate our model using actual data from one factory at Amy's Kitchen and compare the performance of our model to that of the actual operation. We find that our model significantly reduces both inventory levels and stockouts relative to those of the actual operation. In addition, we identify a lower bound on the total costs for all feasible solutions to the problem and measure the effectiveness of our model against this lower bound. We perform sensitivity analysis on some key parameters and assumptions of our modeling approach.     

A LOGIT-MARKOVIAN MODEL OF CONSUMER PURCHASE BEHAVIOR BASED ON EXPLANATORY VARIABLES: EMPIRICAL EVALUATION AND IMPLICATIONS FOR DECISION MAKING*

This study describes and empirically evaluates an approach to modeling purchase behavior that integrates a Logit-Markov-based multivariate brand-choice model structure with stochastic components. Using actual market data for a frequently purchased consumer product obtained from a consumer purchase panel survey, the paper highlights some marketing applications of the model. Given its general structure, the model can aid marketing managers in defining and evaluating target market segments and in assessing the impact of alternative marketing strategies.     

Estimation of Nonlinear Models in the Presence of Measurement Error*

Techniques used in decision sciences and business research to estimate interactions between latent variables are limited in controlling for measurement error. This article uses a latent structure modeling approach that substantially controls for measurement error in nonlinear relationships. The results of this technique are compared to the results obtained applying hierarchical regression analysis and the impact of measurement error is assessed. The paper provides a unique assessment of the validity of the multi-attribute attitude model. The validity of the multiplicative rule in the model is supported.     

多品种集约生产计划问题的模糊方法

提出具有模糊需求量和模糊能力约束以及资本水平约束的多品种类集约生产计划问题 的模糊优化模型及模糊解方法. 通过对模糊需求量和模糊等式的描述,提出了模糊需求环境下 生产- 库存平衡方程的两种等价的描述方法, 并给出了模糊等式的实用解释. 建立了具有模 糊需求量和模糊能力约束集约生产计划问题的优化模型FMAPP ,并给出了求解模型的参数规 划方法.     

Integrated Direct and Indirect Flood Risk Modeling: Development and Sensitivity Analysis

In this article, we propose an integrated direct and indirect flood risk model for small‐ and large‐scale flood events, allowing for dynamic modeling of total economic losses from a flood event to a full economic recovery. A novel approach is taken that translates direct losses of both capital and labor into production losses using the Cobb‐Douglas production function, aiming at improved consistency in loss accounting. The recovery of the economy is modeled using a hybrid input‐output model and applied to the port region of Rotterdam, using six different flood events (1/10 up to 1/10,000). This procedure allows gaining a better insight regarding the consequences of both high‐ and low‐probability floods. The results show that in terms of expected annual damage, direct losses remain more substantial relative to the indirect losses (approximately 50% larger), but for low‐probability events the indirect losses outweigh the direct losses. Furthermore, we explored parameter uncertainty using a global sensitivity analysis, and varied critical assumptions in the modeling framework related to, among others, flood duration and labor recovery, using a scenario approach. Our findings have two important implications for disaster modelers and practitioners. First, high‐probability events are qualitatively different from low‐probability events in terms of the scale of damages and full recovery period. Second, there are substantial differences in parameter influence between high‐probability and low‐probability flood modeling. These findings suggest that a detailed approach is required when assessing the flood risk for a specific region.