A Priori and A Posteriori Aggregation Procedures to Reduce Model Size in MIP Mine Planning Models

Mine planning models have proved to be very effective in supporting decisions on sequencing the extraction of material in copper mines. These models have been developed for CODELCO, the Chilean state copper mine and used successfully. Here, we wish to develop a corporate model, including all mines of CODELCO. The original models are extremely large MIPs. In order to run a global model, the original models need to be reduced significantly. We develop an approach to aggregate the models. The aggregation is done both on the original data of the mine as well as on the MIP original models. The aggregation is based on clustering analysis. Promising results were obtained with data of a large underground mine.     

A new MIP model for mine equipment scheduling by minimizing maintenance cost

Mining investment has been recognized as capital intensive due mainly to the cost of large equipment. Equipment capital costs for a given operation are usually within the order of hundreds of million dollars but may reach to billion dollars for large companies operating multiple mines. Such large investments require the optimum usage of equipment in a manner that the operating costs are minimized and the utilization of equipment is maximized through optimal scheduling. This optimum usage is required to ensure that the business remains sustainable and financially stable. Most mining operations utilize trucks to haul the mined material. Maintenance is one of the major operating cost items for these fleets as it can reach approximately one hundred million dollars yearly. There is no method or application in the literature that optimizes the utilization for truck fleet over the life of mine. A new approach based on mixed integer programming (MIP) techniques is used for annually scheduling a fixed fleet of mining trucks in a given operation, over a multi-year time horizon to minimize maintenance cost. The model uses the truck age (total hours of usage), maintenance cost and required operating hours to achieve annual production targets to produce an optimum truck schedule. While this paper focuses on scheduling trucks for mining operation, concept can be used in most businesses using equipment with significant maintenance costs. A case study for a large scale gold mine showed an annual discounted (10% rate) maintenance cost saving of over $2M and more than 16% ($21M) of overall maintenance cost reduction over 10 years of mine life, compared with the spreadsheet based approach used currently at the operation.     

基于动态CGE的铁矿砂价格冲击经济效应研究

利用湖南大学—莫纳什大学合作开发的中国动态可计算一般均衡模型—MCHUGE模型,对国际铁矿砂价格冲击的宏观经济影响进行动态的量化分析。模拟结果显示：澳大利亚农业研究署所预测的未来铁矿砂价格年均增长率对中国经济的影响较小,相比于基线预测值,短期里通过增加社会岗位,长期里通过提高资本存量,从而减少了中国经济所受影响的幅度。     

国内外期铜价格之间的长期记忆成分和短期波动溢出效应

本文区分国内外期铜市场价格的长记忆成分和短期波动溢出效应,采用信息共享模型和永久一瞬时模型分离出不同期铜市场价格间的长记忆成分,得到不同市场期铜价格对"隐含有效价格"的贡献度;而且,利用t分布的BEKK模型分析两个市场期铜价格的短期波动溢出.特别,我们在BEKK基础上定义了不同变量间的波动溢出项,对两个市场期铜价格的波动溢出进行了度量.根据测算结果,我们发现国内外期铜价格有着紧密的联系,无论在长期,还是在短期,国外市场期铜价格的影响力都较大.     

Using aggregation to optimize long-term production planning at an underground mine

Motivated by an underground mining operation at Kiruna, Sweden, we formulate a mixed integer program to schedule iron ore production over multiple time periods. Our optimization model determines an operationally feasible ore extraction sequence that minimizes deviations from planned production quantities. The number of binary decision variables in our model is large enough that directly solving the full, detailed problem for a three year time horizon requires hours, or even days. We therefore design a heuristic based on solving a smaller, more tractable, model in which we aggregate time periods, and then solving the original model using information gained from the aggregated model. We compute a bound on the worst case performance of this heuristic and demonstrate empirically that this procedure produces good quality solutions while substantially reducing computation time for problem instances from the Kiruna mine.     

基于区间效率的贷款定价研究

以存款利息支出率、费用支出率、预期违约损失率、目标利润率等4个定价指标作为输入,以贷款利率作为输出,采用支持向量机回归算法建立基于区间效率的贷款定价模型.创新与特色一是通过区间数形式来反映预期违约损失率、目标利润率、费用支出率等,改变了现有研究将目标利润、贷款费用、违约损失等变量看作确定性数值来定价的现状.使贷款利率更具有竞争性.二是通过比较不同核函数、核参数下的训练样本的贷款效率区间与合理的贷款效率区间的匹配程度,确定贷款定价模型最优的核函数和核参数,进而建立了贷款定价模型.间接解决了在考虑贷款价格能否被银行、客户接受情况下贷款利率确定的问题.     

非贵金属期货市场对白银期货市场的贝叶斯非线性效应研究

选取2012年8月13日至2013年9月16日的各金属期货周收盘价构成的平衡面板数据,以黄金期货价格为转换变量,本文利用贝叶斯面板平滑转换模型探索非贵金属与白银期货可能存在的非线性关系.研究结果表明,铜、铝、螺纹钢市场与白银期货市场具有时变的非线性关系.因此,投资者可以根据非贵金属期货价格走势更好的对白银期货投资价值进行评估,从而提高投资决策的科学性.     

带有随机产出和广告投入的Newsboy模型

首次将随机产出和广告投入同时引入到Newsboy模型中,分别在乘积形式随机产出和加和形式随机产出情况下,建立带有广告费用的最优决策模型,通过分析得出如下结论:在乘积随机产出情况下,随着广告费用的不断增加,最优计划生产量在快速增加;而在加和形式随机产出情况下,随着广告费用不断增加时,最优计划生产量也在不断增加,但其增加的速率较小。最后,指出乘积形式的随机产出适用于刚上市的新产品,而加和形式的随机产出适用于品牌产品。     

Multi-product production planning: A goal programming approach

Cost minimization multi-product production problems with static production resource usage and internal product flow requirements have been solved by linear programming (LP) with input/output analysis. If the problem is complicated by interval resource estimates, interval linear programming (ILP) can be used. The solution of realistic problems by the above method is cumbersome. This paper suggests that linear goal programming (LGP) can be used to model a multi-product production system. LGP's unique modeling capabilities are used to solve a production planning problem with variable resource parameters. Input/output analysis is used to determine the technological coefficients for the goal constraints and is also used to derive an information sub-model that is used to reduce the number of variable resource goal constraints. Preliminary findings suggest that the LGP approach is more cost-efficient (in terms of CPU time) and in addition provides valuable information for aggregate planning.     

煤矿安全生产法律法规实效性的(安全作用)虚拟变量模型分析

为了弄清我国煤矿安全生产因素对安全生产的影响程度,建立了百万吨煤死亡率与影响煤矿安全生产五个主要指标(采煤机械化程度、煤矿工程技术人员配备率、全国人均GDP、原煤生产全员工效和吨煤基本建设投入)之间的多元回归模型,结果显示采煤机械化程度、吨煤基本建设投入和全国人均GDP对百万吨煤死亡率有着较大影响,其中全国人均GDP对百万吨煤死亡率起着负的作用.为了比较分析20世纪90年代以来有关煤矿安全生产的一些重要法律的法律法规实效性的安全作用的方向和大小,建立了多元虚拟变量回归模型,研究表明,有关煤矿安全生产的"三法律一条例"实效性的安全作用平均使得百万吨煤死亡率降低0.895人;"三法律一条例"的实效性表明,法律条款中的经济处罚和制裁条款与经济发展水平越符合,法治力度越强,其执行效果越好.     

贴现率不确定条件下矿产资源最优开采及资源税研究

贴现率在研究矿产资源代际优化配置时起着非常重要的作用。首先,在贴现率具有不确定性的条件下,讨论了矿产资源的最优开采问题,给出了矿产资源价格期望变化率;其次研究了贴现率具有不确定性、市场存在垄断时最优资源税设定问题。结果显示,贴现率的不确定性降低了资源价格期望变化率,但从价资源税不受其影响,从量资源税与不确定性程度之间存在反向变动关系。     

OPTIMAL R&D FOR NONRENEWABLE RESOURCES: THE CASE OF COST REDUCING TECHNOLOGY

A model is developed to determine optimal R&D spending and completion time when R&D results in lower extraction costs of a nonrenewable resource deposit. Examples of R&D projects for which the model is designed are in-situ leaching for mining and carbon dioxide injection in petroleum. The model is a combined R&D/nonrenewable resource model (CM). Results from the CM are compared to simulations of an R&D model which ignores the nonrenewable resource. The comparison demonstrates the importance of including resource parameters in the R&D spending model. The CM extends the literature by considering R&D spending and exhaustible natural resource production simultaneously. It demonstrates the importance of including the resource deposit when R&D affects the deposit. This is important because more accurate models of R&D will increase the profitability of the R&D projects.     

A heuristic approach for the stochastic optimization of mine production schedules

Traditionally, mining engineers plan an open pit mine considering pre-established conditions of operation of the plant(s) derived from a previous plant optimization. By contrast, mineral processing engineers optimize the processing plants by considering a regular feed from the mine, with respect to quantity and quality of the materials. The methods implemented to optimize mine and metallurgical plans simultaneously are known in the mining industry as global or simultaneous optimizers. The development of these methods has been of major concern for the mining industry over the last decade. Some algorithms are available in commercial mining software packages however, these algorithms ignore the inherent geological uncertainty associated with the deposit being considered, which leads to shortfalls in production, quality, and expected cashflows. This paper presents a heuristic method to generate life-of-mine production schedules that consider operating alternatives for processing plants and incorporate geological uncertainty. The method uses iterative improvement by swapping periods and destinations of the mining blocks to generate the final solution. The implementation of the method at a copper deposit shows its ability to control mine and processing capacities while increasing the expected net present value by 30% when compared with a solution generated using a standard industry practice.     

流动性过剩对物价和产出的动态冲击效应分析

本文运用结构向量自回归(SVAR)模型方法,研究了我国流动性过剩对物价和产出所产生的动态冲击效应。主要结论是:流动性过剩正冲击对物价仅有短期正效应,即在短期促使物价上涨。流动性过剩正冲击对产出有正效应,而且其效果是中长期有效的,即流动性过剩在中长期促进产出增长。货币供应量M_2对产出的增长的效力相对较大,而货币供应量M_1对物价的影响力相对较大。     

Expectations equilibria with dispersed forecasts

A dispersion condition for traders' forecasts in a general equilibrium model with uncertainty and asymmetric information yields improved results for some (microeconomic) situations in which rational expectations equilibria need not exist. The hypothesis of suitably dispersed forecasts implies that consumers' aggregate excess demand is a continuous function and therefore a fixed point theorem may be applied to obtain a price vector (for each state of the world) such that markets clear. Stronger assumptions give existence of approximately rational expectations equilibria and the convergence of forecast distributions to rational expectations.     

Neural network as a simulation metamodel in economic analysis of risky projects

An artificial neural network (ANN) model for economic analysis of risky projects is presented in this paper. Outputs of conventional simulation models are used as neural network training inputs. The neural network model is then used to predict the potential returns from an investment project having stochastic parameters. The nondeterministic aspects of the project include the initial investment, the magnitude of the rate of return, and the investment period. Backpropagation method is used in the neural network modeling. Sigmoid and hyperbolic tangent functions are used in the learning aspect of the system. Analysis of the outputs of the neural network model indicates that more predictive capability can be achieved by coupling conventional simulation with neural network approaches. The trained network was able to predict simulation output based on the input values with very good accuracy for conditions not in its training set. This allowed an analysis of the future performance of the investment project without having to run additional expensive and time-consuming simulation experiments.     

Cooperative and Non-Cooperative Differential Game Solutions to an Investment and Pricing Problem

A monopoly possesses a finite stock of a resource and wishes to determine an optimal pricing policy. The competitive fringe invests in production capacity and wishes to select an optimal investment rate. Demand towards the monopoly depends on price as well as on the sales rate of the competition. Modelling the situation as a differential game, non-cooperative (Nash and Stackelberg) and cooperative (Pareto) equilibria are determined. Owing to the special structure of the game, these solutions can be found in closed form.     

政治关系对企业投资决策的影响分析:基于发展中国家视角

基于发展中国家对外直接投资规模越来越大,探讨了政治关系对海外直接投资的影响.通过设定"政治关系"因子,借助经济学市场均衡理论,在分析两类生产企业以及一类用户的基础上,通过求解利润最大化的市场价格和产量,研究了企业潜在利润和生产选择.进而得到:企业的政治关系越强,其参与对外直接投资的临界生产率就越低,使之参与对外直接投资的可能性大大增加.     

NONMARKET RESOURCE VALUATION: A BILEVEL OPTIMIZATION APPROACH

The social value of a common property/open access resource is in general different from the value attributed by individual users. Therefore, public intervention in the form of prices, quotas and marketable licenses has often been necessary to prevent overexploitation of such resources. This paper addresses the pricing issue. The existing mathematical programming studies in the resource economics literature suggest using the shadow price information obtained from an aggregate model where the sum of net returns to individual users and the management authority is maximized. When the policy maker's objective takes a different form, however, the shadow price strategy may result in a socially suboptimum or infeasible resource utilization. A bilevel optimization approach is proposed in this paper where the price of the resource is introduced as a policy variable and the optimizing behavior of individual users is considered as an explicit constraint in a global optimization problem. An empirical application of the proposed approach to the steady state management of a large scale irrigation system is presented.     

不完全市场的保险定价研究

完全市场上的保险定价问题是人们比较熟悉的研究内容,但它不符合市场实际.本文在不完全市场上研究保险定价的问题.通过对累积保险损失的分析,建立在累积赌付下的保险定价模型;基于对一个无风险资产和有限多个风险资产的投资,建立保险投资定价模型.通过变形,得到相应的保险价格的倒向随机微分方程,并利用倒向随机微分方程的理论和方法,得到了相应的保险价格公式.最后,给出释例进行了分析.本文的研究,不用考虑死亡率、损失的概率分布等因素,为保险定价提供了新的思路,丰富了有限的保险定价方法.