System Dynamics Modelling for Residential Energy Efficiency Analysis and Management

A System Dynamics model to simulate the substitution of installed household appliances by more efficient ones is presented. The model allows the construction of scenarios and also the analyses of several other issues such as: alternatives for technology penetration, electricity consumption growth, gas consumption growth and effects of pricing policies on various energy demands. The proposed methodology has been applied to assist the decision process in relation to gas penetration policies. The model also supports policy making on energy efficiency and it allows the calculation of total energy savings under different scenarios. Furthermore, government underpricing policies on tariffs and appliance acquisition (longer loan terms, lower interest rates and grace periods) may also be analysed.     

Portfolio optimization in a Lévy market with intertemporal substitution and transaction costs

We investigate an infinite horizon investment-consumption model in which a single agent consumes and distributes her wealth between a risk-free asset (bank account) and several risky assets (stocks) whose prices are governed by Lévy (jump-diffusion) processes. We suppose that transactions between the assets incur a transaction cost proportional to the size of the transaction. The problem is to maximize the total utility of consumption under Hindy-Huang-Kreps intertemporal preferences. This portfolio optimisation problem is formulated as a singular stochastic control problem and is solved using dynamic programming and the theory of viscosity solutions. The associated dynamic programming equation is a second order degenerate elliptic integro-differential variational inequality subject to a state constraint boundary condition. The main result is a characterization of the value function as the unique constrained viscosity solution of the dynamic programming equation. Emphasis is put on providing a framework that allows for a general class of Lévy processes. Owing to the complexity of our investment-consumption model, it is not possible to derive closed form solutions for the value function. Hence, the optimal policies cannot be obtained in closed form from the first order conditions for the dynamic programming equation. Therefore, we have to resort to numerical methods for computing the value function as well as the associated optimal policies. In view of the viscosity solution theory, the analysis found in this paper will ensure the convergence of a large class of numerical methods for the investment-consumption model in question.     

Optimisation of pneumatic circuit aimed at improving the vibro-isolation properties of seat suspension

The object of a numerical simulation and optimisation is the seat with a visco-elastic passive suspension, with improved vibro-isolation properties by means the multi-criteria optimisation. Basing on the verified passive seat suspension model, a modification of the pneumatic circuit in order to help the working machines operators against vibration is considered. The root mean square (RMS) acceleration measured at the seat and the maximum relative displacement of the seat suspension are minimised as the chosen vibro-isolation criteria. (© 2009 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

消费者非均匀偏好条件下高校项目开发策略

为了探究教育项目消费者随机需求条件下的不同层次高校的竞优策略, 运用Stackelberg博弈方法, 构建了消费者偏好服从非均匀分布的不同层次高校开发同类教育项目的定位设计模型, 分析了消费者偏好行为对教育项目收益的影响规律以及双方的竞优策略。结果显示, H型高校(声誉较高)不受消费者偏好等市场因素影响, 始终选择最大差异化策略。L型高校(声誉较低)在消费者无差异偏好偏向自己一方时也不受市场因素影响采取最大差异化策略; 而在消费者无差异偏好偏向它方时, 若市场需求概率小于0.5则选择最大差异化策略, 否则其决策将受到自身初始位值、市场概率等因素的综合影响, 并适时选择最大差异化、有限差异化或有限趋同化策略。     

以旧换新消费比例对闭环供应链的影响

从产品进入市场到普及的过程中,以旧换新消费的比例逐渐增大。该文从消费者、闭环供应链的规模和企业三个视角分析了消费结构变化对闭环供应链的影响。研究表明,随着以旧换新消费比例的增大:初次消费者和以旧换新消费者的消费者剩余均减少,且初次消费者减少较多;正向供应链的规模逐渐减小,而逆向供应链从无到有,规模逐渐增大,直至正向供应链和逆向供应链的规模相等;制造商的利润逐渐增大,而回收商的利润从无到有,并逐渐增大至极值后有所下降。     

Impact of compressor failures on gas transmission network capability

National Grid, the gas operator in the United Kingdom, has experienced challenges in evaluating the capability of its gas transmission network to maintain function in the event of risks particularly to withstand the impact of compressor failures. We propose a mathematical programming model to support the operator in dealing with the problem. Several solution techniques are developed to solve the various versions of the problem efficiently. In the case of little data on compressor failure, an uncertainty theory is applied to solve this problem if the compressor failures are independent; while a robust optimisation technique is developed to solve it when they are not. Otherwise, when there are data on compressor failure, Monte Carlo simulation is applied to find the expected capability of the gas transmission network. Computational experiments, carried out on a case study at National Grid, demonstrate the efficiency of the proposed model and solution techniques. A further analysis is performed to determine the impact of compressor failures and suggest efficient maintenance policies for National Grid.     

一种电子商务环境下耐用品的动态定价模型与策略

针对电子商务环境下消费者对价格歧视的抗拒问题,以及耐用品生命周期长、产品需求依赖于时间、价格等特点,提出了一种动态定价模型与策略。该模型通过构造转移概率矩阵,推导出在线消费者浏览到耐用品的不同价格状态下的概率,接着根据消费者多阶段效用函数分析消费者的购买决策行为,进而给出零售商利润达到最大化时的最优定价策略集合。为了验证模型与策略的有效性,通过数值模拟实验,分析模型主要参数变化对最优定价策略的影响。研究发现当效用折扣因子越高,零售商应该降低促销频率和高价格并且提高低价格,从而诱导高端消费者在高价格购买产品。折扣效用因子大小还决定了网上零售商是否要隐藏自己的促销概率。     

Time consistent Markov policies in dynamic economies with quasi-hyperbolic consumers

We study the question of existence and computation of time-consistent Markov policies of quasi-hyperbolic consumers under a stochastic transition technology in a general class of economies with multidimensional action spaces and uncountable state spaces. Under standard complementarity assumptions on preferences, as well as a mild geometric condition on transition probabilities, we prove existence of time-consistent solutions in Markovian policies, and provide conditions for the existence of continuous and monotone equilibria. We present applications of our methods to habit formation models, environmental policies, and models of consumption under borrowing constraints, and hence show how our methods extend the results obtained by Harris and Laibson (Econometrica 69:935–957, 2001) to a broad class of dynamic economies. We also present a simple successive approximation scheme for computing extremal equilibrium, and provide some results on the existence of monotone equilibrium comparative statics in the model’s deep parameters.     

居民用户峰谷分时气价模型及其优化求解方法

针对天然气的居民用户制定合理的峰谷分时气价,能有效地削峰填谷,从而保证燃气管道安全稳定地运行。本文构建用户需求响应和满意度函数,并在此基础上建立以最小化最大峰负荷和峰谷负荷差,及最大化用户满意度为目标的需求侧峰谷分时气价优化模型。采用蚁群算法对模型进行求解,该算法收敛性较好,同时也避免局部最优的缺点。算例结果表明,在兼顾公平与效率的前提下,峰谷分时气价模型能有效地降低最大峰负荷和峰谷负荷差,同时存在最优的峰、平、谷价格,使得用户满意度最大;另外本文也验证了模型的有效性及可行性。此方法为天然气合理定价机制的建立及政策的制定提供了理论依据。     

Advance selling to strategic consumers

Advance selling of goods and services is a form of separating purchase from consumption. It is often employed when consumers are uncertain about their consumption utilities until a short time period before consumption. A book to be released, a concert to attend, or a cruise to take are some examples. Invariably, in consumers’ mind inventory availability (of copies, seats, or rooms) is a concern. In this paper we study a retailer’s inventory and pricing decisions in an advance selling scenario that involves consumers who are strategic. Some consumers not only consider advance and spot prices, but also the uncertainty in future availability of the product (during the spot period) and in their consumption utility from it. We characterize the optimal inventory management and pricing policies, and discuss several interesting aspects of the solution. For example, it can be optimal for the retailer to limit advance sales even if there is more demand for it, and it can be optimal for the retailer to limit its inventory even though there is more capacity to keep it, but not both.     

A simulated annealing algorithm for transient optimization in gas networks

In this paper we present a simulated annealing approach for the gas network optimization problem. A gas network consists of a set of pipes to transport the gas from the sources to the sinks whereby gas pressure gets lost due to friction. Further on there are compressors, which increase gas pressure, and valves. The aim is to minimize fuel gas consumption of the compressors whereas demands of consumers have to be satisfied. The problem of transient (time-dependent) optimization of gas networks results in a highly complex mixed integer nonlinear program. We relax the equations describing the gas dynamic in pipes by adding these constraints combined with appropriate penalty factors to the objective function. A suitable neighborhood structure is developed for the relaxed problem where time steps as well as pressure and flow of the gas are decoupled. Our approach convinces with flexibility and very good computational results.     

Setting expediting repair policy in a multi-echelon repairable-item inventory system with limited repair capacity

Inventory systems with limited repair capacity are affected by congestion externalities, caused by use of a shared service. There is incompatibility between individual and system optimisation in considering congestion externalities. Three models are described that investigate the congestion effect in a multi-echelon inventory system which has two modes of repair, each with a limited repair capacity. An expanding repair policy employed by the bases in order to choose which repair mode to use is described and compared with different expediting policies related to congestion externalities. The expanding repair policy that considers congestion externalities was found to lead to better system performance measurement than an expanding policy with no congestion. The results of the numerical experiment indicate that the model that ignores congestion externalities—that is, the model that measures each base as an individual—leads to poorer performance measurement for every expediting repair policy, and particularly for the optimal expediting repair policy.     

Optimising for energy or robustness? Trade-offs for VM consolidation in virtualized datacenters under uncertainty

Reducing the energy consumption of virtualized datacenters and the Cloud is very important in order to lower CO\( _2 \) footprint and operational cost of a Cloud operator. However, there is a trade-off between energy consumption and perceived application performance. In order to save energy, Cloud operators want to consolidate as many Virtual Machines (VM) on the fewest possible physical servers, possibly involving overbooking of resources. However, that may involve SLA violations when many VMs run on peak load. Such consolidation is typically done using VM migration techniques, which stress the network. As a consequence, it is important to find the right balance between the energy consumption and the number of migrations to perform. Unfortunately, the resources that a VM requires are not precisely known in advance, which makes it very difficult to optimise the VM migration schedule. In this paper, we therefore propose a novel approach based on the theory of robust optimisation. We model the VM consolidation problem as a robust Mixed Integer Linear Program and allow to specify bounds for e.g. resource requirements of the VMs. We show that, by using our model, Cloud operators can effectively trade-off uncertainty of resource requirements with total energy consumption. Also, our model allows us to quantify the price of the robustness in terms of energy saving against resource requirement violations.     

The use of artificial intelligence technique for the optimisation of process parameters used in the continuous casting of steel

The productivity and quality of a continuous caster depend mainly on process parameters, i.e. casting speed, casting temperature, steel composition and cleanliness of the melt, water flow rates in the different cooling zones, etc. This work presents the development of an algorithm, which incorporates heuristic search techniques for direct application in metallurgical industries, particularly those using continuous casting process for the production of steel billets and slabs. This is done to determine the casting objectives of maximum casting rate as a function of casting constraints. These constraints are evaluated with the aid of a heat transfer and solidification model based on the finite difference technique, which has been developed and integrated with a genetic algorithm. The essential parts of continuous casting equipment, which must be subjected to monitoring, as well as a methodology of mathematical model and physical settlements in each cooling region, are presented. The efficiency of the intelligent system is assured by the optimisation of the continuous casting operation by maximum casting rate and defect-free products. This approach is applied to the real dimension of a steel continuous caster, in real conditions of operation, demonstrating that good results can be attained by using heuristic search, such as: smaller temperature gradients between sprays zones, reduction in water consumption and an increase in casting speed.     

考虑消费动机和动态竞争的电影日需求预测模型

提出并验证考虑消费动机和动态竞争的电影日需求预测模型。考虑非粉丝及粉丝型的消费动机,构建电影消费两阶段过程模型;融合该模型和Bass模型,考虑竞争导致市场潜量的动态性,考虑映前被关注度、口碑、节假日对票房的影响,提出电影日需求预测模型。利用2016~2017年上映的电影数据验证该模型,并与Bass模型对比分析。结果显示,该模型预测效果优于Bass模型。因考虑竞争导致的动态市场潜量,考虑粉丝型消费者由续集效应及改编效应导致的动态市场潜量提升,该模型能显著提高预测准确度。利用映前被关注度和电影口碑数据,该模型能实现映前及上映早期的预测。该模型可推广至存在消费动机不同、市场动态竞争的其它短生命周期体验品的需求预测,是对Bass模型的改进。     

“新常态”下的中国天然气消费分析及预测

作为一种优质、高效的绿色能源,天然气在中国能源结构中所占比重逐渐增加。但可再生能源的崛起使得天然气成为过渡能源的选择,天然气消费量的增长趋势不明晰,因此相关企业及部门需要合理、准确的天然气需求预测模型为未来的工作提供指导性信息。基于此,本文首先从经济水平、产业结构、能源结构、天然气价格等方面选取影响天然气消费的12个因素。其次,运用贝叶斯模型平均(BMA)法构建了一个包含相关文献中常用的6个影响因素的基准模型,针对该模型,围绕影响天然气消费量的各种因素,以逐个添加的方式建立对比模型,从备选模型中选出预测精度最高的对未来天然气消费量进行预测。最后,将BMA模型与ARIMA模型、ETS模型、BVAR模型、逐步回归模型以及等权重加权平均模型的预测精度进行对比。结果表明,最优的BMA模型包含了涉及经济水平、产业结构、能源结构、人口因素、天然气价格、天然气供给六个方面9个影响因素,其预测精度优于对比预测模型,且该模型预测 2022年天然气消费量将达到3254.153亿立方米,年均增长率为8%。     

Object-oriented dynamic supply-chain modelling incorporated with production scheduling

In this paper we present a new modelling approach for realistic simulation of supply-chains. It is based on an object-oriented architecture, which enables flexible specification of the supply-chain configuration along with its operational decisions and policies.A model of a generic supply-chain node is developed to capture the features present in all supply-chain entities. The generic node models in detail activities such as inventory control, manufacturing processes and order handling. The supply-chain model is constructed by linking generic nodes and specifying the physical and business attributes of each supply-chain member. The generic-node model may also be linked to external software for greater accuracy, e.g., detailed production scheduling or optimisation.The model provides a fully dynamic simulation of the supply-chain and the effect of various uncertainties can be evaluated through Monte Carlo simulation and other, more efficient, sampling techniques (not described here).A case study is presented to illustrate the applicability of the model. The case study demonstrates how the effect of policy changes on the supply-chain performance under uncertainty can be evaluated before implementation.     

Optimisation of road vehicle passive suspension systems. Part 1. Optimisation algorithm and vehicle model

Numerous problems have in the past been experienced during the development of military vehicle suspension systems. In order to solve some of these problems a two-dimensional multi-body vehicle dynamics simulation model has been developed for computer implementation. This model is linked to a mathematical optimisation algorithm in order to enable the optimisation of vehicle design parameters through the minimisation of a well defined objective function. In part 1 of this paper the concept of multi-disciplinary design optimisation is discussed. This is followed by the presentation of the up to six degrees of freedom vehicle model developed for this study, and a discussion of the specific gradient-based optimisation algorithm selected for the optimisation. In particular the derivation of the set of second-order differential equations, describing the acceleration of the different solid bodies of the vehicle model, is presented. In order to perform the optimisation of the non-linear suspension component characteristics, a six piece-wise continuous and linear approximation is used which is also described in this paper. Part 2 of this study will outline the simulation programme and the qualification of the programme. It will also present a typical case study where the proposed optimisation methodology is applied to improve the damper characteristics of a specific vehicle.     

Vector maximisation and lagrange multipliers

The Lagrangean function for scalar constrained optimisation problems is extended in a directly analogous manner to constrained vector optimisation problems. Some simple saddle point results are presented for vector maxima sets. Conditions are given for the characterisation of the vector maximum set of the original vector problem in terms of the vector maximum sets with respect to the vector Lagrangeans. Finally some attention is given to Lagrangean relaxation for vector optimisation problems as an extension of a result of Everett.     

Coordinated control of distribution supply chains in the presence of fuzzy customer demand

This paper considers a single product inventory control in a Distribution Supply Chain (DSC). The DSC operates in the presence of uncertainty in customer demands. The demands are described by imprecise linguistic expressions that are modelled by discrete fuzzy sets. Inventories at each facility within the DSC are replenished by applying periodic review policies with optimal order up-to-quantities. Fuzzy customer demands imply fuzziness in inventory positions at the end of review intervals and in incurred relevant costs per unit time interval. The determination of the minimum of defuzzified total cost of the DSC is a complex problem which is solved by applying decomposition; the original problem is decomposed into a number of simpler independent optimisation subproblems, where each retailer and the warehouse determine their optimum periodic reviews and order up-to-quantities. An iterative coordination mechanism is proposed for changing the review periods and order up-to-quantities for each retailer and the warehouse in such a way that all parties within the DSC are satisfied with respect to total incurred costs per unit time interval. Coordination is performed by introducing fuzzy constraints on review periods and fuzzy tolerances on retailers and warehouse costs in local optimisation subproblems.