Modelling decentralized decision making in the energy sector

Large linear programming models, which have been widely used to determine the optimal structure of national energy systems, are based on the assumption that there is an absolutely centralized decision making process within the energy system. In this paper an attempt is made to match the real decision structure of a given energy system, by decomposing an LP energy model into smaller models, with the corresponding system decision centres. This is done by applying the ‘transfer price’ algorithm of Dantzing and Wolfe. The ‘master’ problem corresponds to the central planning unit, i.e. a Ministry of Energy, whereas the subproblems correspond to peripheral operating units, i.e. enterprises, usually state owned, which produce and distribute the energy carriers. The optimal plans of the peripheral units are submitted to the central unit, which through the mechanism of pricing of both common resources, inputs and energy services outputs, co-ordinates the overall planning of the energy system. An illustrative example is given referring to the Hellenic national energy system. The research reported is placed within a wider research endeavour, whose objectives and main line of work are also given.     

CAPACITY AND PRODUCTION DECISIONS IN STOCHASTIC MANUFACTURING SYSTEMS: AN ASYMPTOTIC OPTIMAL HIERARCHICAL APPROACH

We present a new paradigm of hierarchical decision making in production planning and capacity expansion problems under uncertainty. We show that under reasonable assumptions, the strategic level management can base the capacity decision on aggregated information from the shopfloor, and the operational level management, given this decision, can derive a production plan for the system, without too large a loss in optimality when compared to simultaneous determination of optimal capacity and production decisions. The results are obtained via an asymptotic analysis of a manufacturing system with convex costs, constant demand, and with machines subject to random breakdown and repair. The decision variables are purchase time of a new machine at a given fixed cost and production plans before and after the purchase. The objective is to minimize the discounted costs of investment, production, inventories, and backlogs. If the rate of change in machine states such as up and down is assumed to be much larger than the rate of discounting costs, one obtains a simpler limiting problem in which the random capacity is replaced by its mean. We develop methods for constructing asymptotically optimal decisions for the original problem from the optimal decisions for the limiting problem. We obtain error estimates for these constructed decisions.     

How to design a financial planning model.

Corporate planning models frequently consist of integrated pro forma income statements, statements of financial position, and cashflow statements. When implemented by utilizing computer-based planning systems, these models allow managers to explore potential decisions in ‘what if?’ planning analyses.The logic of an integrated financial statement planning model can be arranged following either a ‘funds needed to balance approach’ or a ‘direct approach’. With a funds needed to balance approach total assets are set equal to total liabilities plus equities to satisfy this fundamental accounting identity. Logic in such models is often difficult to validate. In the direct approach, total assets are calculated independently of total liabilities plus equities providing an extremely strong test for model validation prior to using the model to assess ‘what if’ alternatives.In this paper, the author discusses the logic of integrated financial planning models and their implementation with computer-based planning systems. The funds need to balance approach and the direct approach are described and contrasted to assist corporate planners in evaluating and selecting a method for constructing the logic of corporate planning models.     

基于信息熵理论的实物期权定价模型及其应用

本文结合实物期权的特点,提出了基于信息熵理论的实物期权定价模型,它根据历史信息和投资者的经验估计期权价格,避免了传统期权定价模型过多依赖于参数选择和假设条件的不足。本文还进一步探讨了该方法与传统期权定价模型间的关系,并合理的解释了企业决策中信息的重要性。最后,结合一个示例,说明了该模型在企业投资决策中的应用价值。     

Regression models of behavior for managerial decision making

A principal problem in systems studies concerns the development of models that will be accepted and used by decision makers in organizations. Regression models derived from managers' past behavior offer promise in overcoming this problem for many repetitive types of decisions. Employing a simulated production planning environment, this paper discusses both the potential usefulness and limitations of such models for understanding and improving decision making in practical applications.     

System dynamics: Portraying bounded rationality

This paper examines the linkages between system dynamics and the Carnegie School in their treatment of human decision making. It is argued that the structure of system dynamics models implicitly assumes bounded rationality in decision making and that recognition of this assumption would aid system dynamicists in model construction and in communication with other social science disciplines. The paper begins by examining Simon's ‘principle of bounded rationality’ which draws attention to the cognitive limitations on the information gathering and processing powers of human decision makers. Forrester's ‘Market Growth Model’ is used to illustrate the central theme that system dynamics models are portrayals of bounded rationality. Close examination of the model formulation reveals decision functions involving simple rules of thumb and limited information content. Finally, there is a discussion of the implications of Carnegie philosophy for system dynamics as it affects communication, model structuring, model analysis and future research.     

Dynamic DEA: A slacks-based measure approach

In data envelopment analysis, there are several methods for measuring efficiency changes over time, e.g. the window analysis and the Malmquist index. However, they usually neglect carry-over activities between two consecutive terms and only focus on the separate time period independently aiming local optimization in a single period, even if these models can take into account the time change effect. In the actual business world, a long time planning and investment is a subject of great concern. For these cases, single period optimization model is not suitable for performance evaluation. To cope with long time point of view, the dynamic DEA model incorporates carry-over activities into the model and enables us to measure period specific efficiency based on the long time optimization during the whole period. Dynamic DEA model proposed by Färe and Grosskopf is the first innovative contribution for such purpose. In this paper we develop their model in the slacks-based measure (SBM) framework, called dynamic SBM (DSBM). The SBM model is non-radial and can deal with inputs/outputs individually, contrary to the radial approaches that assume proportional changes in inputs/outputs. Furthermore, according to the characteristics of carry-overs, we classify them into four categories, i.e. desirable, undesirable, free and fixed. Desirable carry-overs correspond, for example, to profit carried forward and net earned surplus carried to the next term, while undesirable carry-overs include, for example, loss carried forward, bad debt and dead stock. Free and fixed carry-overs indicate, respectively, discretionary and non-discretionary ones. We develop dynamic SBM models that can evaluate the overall efficiency of decision making units for the whole terms as well as the term efficiencies.     

政府补贴方式对绿色供应链制造商减排决策的影响机制

考虑制造商自主研发减排与外包减排任务两种情形,研究政府分别依据减排研发和单位产品减排量进行补贴下供应链的最优决策问题。从供应链制造商的角度,对给定政府补贴方式下,制造商的两种减排决策进行了对比,同时从政府的角度,在制造商特定的减排情形下,两种政府补贴方式的减排效果进行比较。进一步,通过数值仿真分析两种补贴方式下补贴系数对供应链决策的影响。研究结果表明,当政府采取依据减排研发的补贴方式进行补贴时,自主研发减排情形下制造商利润大于外包减排任务情形的利润;当政府采取依据单位产品减排量的补贴方式时,相比外包减排任务,制造商选择自主研发减排均能得到更多的减排量和利润。当制造商自主研发减排时,政府依据减排研发补贴方式比单位产品减排量补贴方式的减排效果更好,但利润较低;当制造商外包减排任务时,两种政府补贴方式的减排效果和利润均相等。通过数值仿真验证了以上结果,同时表明补贴系数对减排效果和利润具有显著影响。以上结论为政府制定合理的补贴方式及企业减排策略的选择提供了理论支撑。     

Performance analysis of a multi-agent scheduling and control system under manufacturing disturbances

This paper is concerned with evaluating the performance of alternative multi-agent approaches to manufacturing planning and control. In order to separate the influence of ‘control algorithm’ from that of ‘control architecture’, a simple local control algorithm is chosen as a common starting point for developing the agent-based system. Two sets of experiments are then reported to evaluate how changes in individual agent characteristics can affect the control system's flexibility and adaptability against disturbances. These experiments show that the manufacturing and control system performance is not affected by architecture if the control algorithm remains fixed, however, altering the characteristics of the control system decision-makers influences both systems’ performance.     

A Multi‐level Dialectical–Paradox Lens for Top Management Team Strategic Decision‐Making in a Corporate Venture

This paper aims to critique the process of corporate‐owned, high‐tech start‐up strategizing through an inductive, longitudinal, case study of ‘UK‐Research‐Tech’. Insights are given through the combined ‘dialectical–paradox’ concept, thereby focusing on where ‘dialectic’ and ‘paradox’ theorizing overlap. This linked iterative, ‘dialogical–dialectic’ research approach also reflects chief executive officer/top management team (CEO/TMT) start‐up dynamics over time. These foci fill important gaps that impede better understanding of dialectical, dialogical and paradoxical forces within strategic decision‐making. As an interpretative tool, they illuminate CEO/TMT strategizing and changing interrelationships affected by broader, volatile, techno‐economic contexts and parent‐company influences on ventures. In this case study, it was found that the CEO's relatively autocratic, parent‐framed approach combined with TMT members' contradictory reactions to create ‘dialectical–paradox’ oppositional forces, eventually only resolved through ‘eleventh hour’ business strategy changes to rescue the venture. This research contributes to more nuanced understandings of corporate‐constrained ventures during early business development from start‐up strategic decisions at parent‐company level to subsequent conditions of more independent dynamic equilibrium. The ‘dialectical–paradox’ conceptual lens contributes an innovative critique of processes affecting strategic decision‐making dynamics. Another important contribution is the empirically inspired conceptual model, developed for use both to guide subsequent case‐study research analyses and as a reflective tool for CEO/TMT strategic decision‐making, especially within corporate‐inspired start‐ups.     

考虑故障停机的生产控制与维修计划联合决策模型

通过生产控制与维修计划协同决策,降低生产成本。首先描述生产过程,分析各项费用。其次,建立了考虑生产过程失控、故障率和故障停时间的生产过程控制、生产计划优化和维修管理联合优化决策的模型。通过模型求解,联合制定出生产过程检查策略、生产计划（经济生产批量、生产批次）以及维修计划（PM间隔期）,实现单位时间内总费用最低的目标。再次,案例研究,分析生产过程失控、故障率和故障停机时间对于经济生产批量、生产过程检查策略和生产系统维修计划的影响。该模型从理论上解决了生产过程控制、生产计划优化和维修管理联合优化决策难题,对于指导企业制定生产计划和生产系统的检修计划,进而提高产品质量、降低生产成本、确保准时交货都具有指导意义和实用价值。     

基于产品生命周期的多阶段剩余收益项目决策模型

剩余收益模型（Residual Income Model,RIM）是评估公司权益价值的经典模型,特别地,奥尔森系列剩余收益模型由于可以利用历史财务与会计数据而得到广泛运用。本文在一般剩余收益模型的基础上,运用规范研究、逻辑推理等方法,基于产品生命周期理论,即项目处于产品生命周期的不同阶段时,其净资产收益率不同,在增长期的净资产收益率持续上升,衰退期的净资产收益率持续下降,而成熟期的净资产收益率则围绕行业平均水平波动,从理论上就项目投资价值的评估构建了多阶段剩余收益项目决策模型,并就所构建的多阶段剩余收益项目决策模型进行参数赋值分析。研究结果表明该新构建的决策模型具有较好的理论和运用价值,可以作为一种有效的项目投资决策模型。本文的研究一是拓展了剩余收益模型的应用,从主要用于对公司权益价值的估值拓展至对项目投资决策的评估;二是有利于寻求项目投资决策的价值最大化。     

Production planning in practice

The changes and pressures facing the manufacturing and engineering industries today are increasing the importance of effective aggregate manpower and production planning. Several different theoretical optimisation models to tackle this problem have been described in detail in the literature but there have been few applications of them in practice.The reasons for this are many but include: the difficulty in expressing managements' conflicting and mixed objectives in an objective function; the necessity to oversimplify real life systems to enable these methods to be used; the simplistic approach to manpower planning used in these models; the difficulty in gaining managements' acceptance and finally the fact that what management actually wants is a tool to assist them in planning and decision making.What is being used by many managements is a case-study deterministic simulation model. Many companies are adopting this type of model for all types of planning and twelve out of twenty-seven companies visited in a research project described in this paper were using this type of model for aggregate manpower and production planning. It is proving to be an effective management tool and is being readily accepted principally because modern specialised financial modelling languages are enabling these models to be built, understood and used by non-specialist managers.     

A Study on a Sequential One‐Defender‐N‐Attacker Game

Government usually faces threat from multiple attackers. However, in the literature, researchers often model attackers as one monolithic player who chooses whether to attack, how much investment to spend, and on which target, instead of treating multiple attackers as independent agents. This modeling strategy may potentially cause suboptimal defense investment if the attackers have vastly different interests and preferences and may not be combined as one in theory. In this article, we develop a sequential game with complete information. This model considers one defender explicitly dealing with multiple unmergeable attackers. Thorough numerical experiments are conducted using ratio and exponential contest success functions under different scenarios. The result is also contrasted with the corresponding single attacker model to study the effect of mishandling multiple attackers. The propositions and observations drawn from the numerical experiments provide insights for government decision making with a better understanding of the attackers' behavior.     

一种决策者判断一致性的聚类方法

对于产量为模糊区间数的生产计划群决策问题,考虑不同产品生产的优先度和决策者权重对决策者判断一致性度量的影响,给出了相对加权一致度的一种计算方法。当群决策的结果不一致时,提出了依据相对加权一致度对决策者进行聚类的方法,并给出了每一类决策者决策结果的综合方法。最后通过算例说明了方法的应用过程。     

A Learning Real Options Framework with Application to Process Design and Capacity Planning

This paper studies the impact of learning on a multi‐staged investment scenario. In contrast to other models in the real options literature in which learning is viewed as a passive consequence of the delay period, this paper quantifies information acquisition by merging statistical decision theory with the real options framework. In this context, real option attributes are discussed from a Bayesian perspective, thresholds are identified for improved decision‐making, and information's impact on downstream decision‐making is discussed. Using real data provided by a firm in the aerospace maintenance, repair, and overhaul industry, the methodology is used to guide a multi‐phased irreversible investment decision involving process design and capacity planning.     

Major capital decisions and technological change

This paper reviews a wide array of the analytical approaches to major capital decision-making available in the literature; indicates some of their weaknesses, especially when major technological changes are involved; suggests some modifications to improve their usefulness; and illustrates some of the additional benefits offered by such redesigned models The approaches examined are: neo-classical, including certainty and uncertainty models; behavioral, including organizational and simulation models; and financial, including evaluative and resource allocation models.After reviewing some of the practical issues confronted in the decision making process a modified general framework is presented to help strengthen the analysis of proposed capital projects Finally, bases are suggested for integrating evaluative investment criteria with the production capabilities embodied in major capital facilities and engendered by major technological innovations.     

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.     

Earnings per share is a poor indicator of performance

One of the greatest dangers in corporate financial planning is failing to separate investment decision making from financial policy, because poor quality investments can appear to be desirable as a result of the particular financing vehicle employed. Management's focus of attention should not be rates of growth and earnings per share or return on net worth. Rather, the most important measure of corporate performance is the rate of return on total capital employed. The paper identifies the dangers of employing an earnings per share criterion for evaluating corporate performance, and suggests an alternative: focusing on a company's free cash flow, net operating profits after taxes minus the amount of new capital investment required in order to generate future profits. The author presents an analytical framework employing his free cash flow concept which can be applied to pricing and financing acquisitions.     

Artificial Intelligence and Generalized Qualitative-Response Models: An Empirical Test on Two Audit Decision-Making Domains

Machine learning methods are currently the object of considerable study by the artificial intelligence community. Research on machine learning carries implications for decision making in that it seeks computational methods that mimic input-output behaviors found in classes of decision-making examples. At the same time, research in statistics and econometrics has resulted in the development of qualitative-response models that can be applied to the same kind of problems addressed by machine-learning models—particularly those that involve a classification decision. This paper presents the theoretical structure of a generalized qualitative-response model and compares its performance to two seminal machine-learning models in two problem domains associated with audit decision making. The results suggest that the generalized qualitative-response model may be a useful alternative for certain problem domains.