Chance constrained programming models for refinery short-term crude oil scheduling problem

The main objective of this work is to put forward chance constrained mixed-integer nonlinear stochastic and fuzzy programming models for refinery short-term crude oil scheduling problem under demands uncertainty of distillation units. The scheduling problem studied has characteristics of discrete events and continuous events coexistence, multistage, multiproduct, nonlinear, uncertainty and large scale. At first, the two models are transformed into their equivalent stochastic and fuzzy mixed-integer linear programming (MILP) models by using the method of Quesada and Grossmann [I. Quesada, I E. Grossmann, Global optimization of bilinear process networks with multicomponent flows, Comput. Chem. Eng. 19 (12) (1995) 1219–1242], respectively. After that, the stochastic equivalent model is converted into its deterministic MILP model through probabilistic theory. The fuzzy equivalent model is transformed into its crisp MILP model relies on the fuzzy theory presented by Liu and Iwamura [B.D. Liu, K. Iwamura, Chance constrained programming with fuzzy parameters, Fuzzy Sets Syst. 94 (2) (1998) 227–237] for the first time in this area. Finally, the two crisp MILP models are solved in LINGO 8.0 based on scheduling time discretization. A case study which has 267 continuous variables, 68 binary variables and 320 constraints is effectively solved with the solution approaches proposed.     

Stochastic chance constrained mixed-integer nonlinear programming models and the solution approaches for refinery short-term crude oil scheduling problem

Stochastic chance constrained mixed-integer nonlinear programming (SCC-MINLP) models are developed in this paper to solve the refinery short-term crude oil scheduling problem which concerns crude oil unloading, mixing, transferring and multilevel inventory control under demands uncertainty of distillation units. The objective of these models is the minimum expected value of total operation cost. It is the first time that the uncertain demands of Crude oil Distillation Units (CDUs) in these problems are set as random variables which have discrete and continuous joint probability distributions. This situation is close to the real world industry use. To reduce the computation complexity, these SCC-MINLP models are transformed into their equivalent stochastic chance constrained mixed-integer linear programming models (SCC-MILP). Stochastic simulation and stochastic sampling technologies are introduced in detail to solve these complex SCC-MILP models. Finally, case studies are effectively solved with the proposed approaches.     

国际原油价格预测的双层随机整数规划模型、算法及应用

根据国际原油价格近期数据及原油价格变化量,给出了国际原油价格改变量的状态转移概率(或频率)矩阵.依此提出以国际原油价格预测误差的期望与方差最小为最优目标,建立国际原油价格预测的双层随机整数规划,并论述该优化问题最优解的存在性, 根据约束特性构造了优化算法.同时按照国内现行成品油定价机制, 提出的优化算法,对国内成品油调价进行了预测,实证分析表明提出的模型与优化算法具有一定的预测精度和较好的实用性.     

Forecasting the volatility of crude oil futures using intraday data

We use the information in intraday data to forecast the volatility of crude oil at a horizon of 1–66 days using a variety of models relying on the decomposition of realized variance in its positive or negative (semivariances) part and its continuous or discontinuous part (jumps). We show the importance of these decompositions in predictive (in-sample) regressions using a number of specifications. Nevertheless, an important empirical finding comes from an out-of-sample analysis which unambiguously shows the limited interest of considering these components. Overall, our results indicates that a simple autoregressive specification mimicking long memory and using past realized variances as predictors does not perform significantly worse than more sophisticated models which include the various components of realized variance.     

A RAPID APPROXIMATION FOR PREDICTING THE HYDROCARBON DISCOVERY RATE: PART 1. ASSESSING THE ACCURACY

The hydrocarbon discovery prediction problem is important to firms having to make decisions about the deployment of scarce exploration resources. Traditional methods for estimating the discovery rate rely on the completion of time consuming simulation experiments. A rapid approximation that does not require the completion of simulation exists and has been shown to have some promise as a prediction tool. This paper investigates the accuracy of the approximation method under a wide variety of distributional and drilling efficiency assumptions. The results indicate that the approximation produces predictions close to those of simulation under most of the tested conditions. This suggests that resource exploration firms could conveniently use the method for a wide variety of planning purposes without incurring the same costs in time and personnel required for simulation.     

A RAPID APPROXIMATION FOR PREDICTING THE HYDROCARBON DISCOVERY RATE: PART 2. IMPROVING THE ACCURACY

In Part 1 of this paper, we noted the systematic errors in the estimates of means and standard deviations produced by a rapid approximation applied to a model of hydrocarbon discovery. In Part 2, we apply regression to predict the approximation errors, as functions of model parameters and approximation output. With the regression model, we can correct much of the error in the approximation, as we illustrate with data from the Nisku-Shelf play of western Canada.     

我国原油价格与外国原油价格的波动溢出效应——基于DCC-MGARCH模型分析

本文利用扩展的4维(E)DCC-MGARCH(1,1)模型,分析了四个原油市场(Brent、WTI、Dubai、China)之间的相互波动溢出效应。研究表明,Brent、WTI原油市场对我国市场均有显著的单向波动溢出效应,WTI原油市场比Brent原油市场对我国原油市场的波动溢出效应更明显。我国和美国原油市场波动都是暂时的,而Brent原油市场波动性是持久的。我国原油市场对Dubai原油市场有单向的波动溢出效应。结果还显示,Brent与WTI原油市场有双向波动溢出效应,Brent的波动溢出效应小于WTI波动溢出效应。     

中缅原油管道贯通对进口原油海上运输成本的影响分析

研究了中缅原油管道贯通对我国进口原油海上运输成本的影响.首先分析了我国的主要原油进口地、进口量和海上运输航线等信息,然后选择了三种不同型号油轮,并调查了其载重量、航速、日租金等数据.以不同型号油轮的运输航次及各条航线上的实际运输量为决策变量,总租金(总运输成本)最小化为目标函数,分别建立了中缅原油管道贯通前后我国进口原油海上运输问题的数学模型,并分别给出了求解方法.最后,根据实际统计数据进行计算,分别求出了中缅原油管道贯通前后我国原油海上运输的总成本,结果显示,中缅原油管道贯通后我国进口原油的海上运输成本将降低4.95%.     

事件对国际石油价格影响的时间序列分析

用近来经济分析中应用较多的现代时间序列分析方法 ,以虚拟变量描述突发事件 ,用 ARMAX模型分析事件对国际原油价格的影响 ,并对今年海湾战争后原油价格的趋势进行预测     

基于EVT-CAViaR模型的原油价格极端风险度量

国际原油价格剧烈波动催生了对油价风险管理需求,在此背景下,科学有效地度量油价风险具有突出的现实意义.以WTI原油每日对数收益率为对象,采用EVT-CAViaR模型度量原油价格极端风险.结果表明:WTI原油市场呈现典型的"杠杆效应"与"高峰厚尾"特征.同时,在测算极端市场风险时,EVT-CAViaR模型有较强的预测风险能力,是一种可靠的油价风险度量工具.     

Profit-based generation resource planning

This paper presents an optimal generation resource planningmodel based on an expected level of revenue, operation and maintenancecosts, transmission charges, load curtailment costs, and theexpected level of system reliability. The model considers thevolatility of market prices for electricity and fuel, variousoptions for securing investment loans, construction lead time,expected load growth, and transmission congestion costs as majorincentives for adding generating capacity to power systems.The proposed planning algorithm will analyse possible sitesand markets for new generators, various unit types and capacities,operating constraints, planned and forced outages, timing forthe addition of new units, and steps for the decommissioningof old generators. The solution approach is based on the extendedBender decomposition technique. A modified IEEE 30-bus casestudy is presented and discussed to exhibit the effectivenessof the proposed resource planning approach.     

MIP models for resource-constrained project scheduling with flexible resource profiles

This paper addresses the resource-constrained project scheduling problem with flexible resource profiles (FRCPSP). Such a problem often arises in many real-world applications, in which the resource usage of an activity is not merely constant, but can be adjusted from period to period. The FRCPSP is, therefore, to simultaneously determine the start time, the resource profile, and the duration of each activity in order to minimize the makespan, subject to precedence relationships, limited availability of multiple resources, and restrictions on resource profiles. We propose four discrete-time model formulations and compare their model efficiency in terms of solution quality and computational times. Both preprocessing and priority-based heuristic methods are also applied to compute both upper and lower bounds of the makespan. Our comparative results show significant dominance of one of the models, the so-called “variable-intensity-based” model, in both solution quality and runtimes.     

Modelling recruitment training in mathematical human resource planning

This paper deals with mathematical human resource planning; more specifically, it suggests a new model for a manpower‐planning system. In general, we study a k‐classed hierarchical system where the workforce demand at each time period is satisfied through internal mobility and recruitment. The motivation for this work is based on various European Union incentives, which promote regional or local government assistance programs that could be exploited by firms not only for hiring and training newcomers, but also to improve the skills and knowledge of their existing personnel. In this respect, in our augmented mobility model we establish a new ‘training/standby’ class, which serves as a manpower inventory position for potential recruits. This class, which may very well be internal or external to the system, is incorporated into the framework of a non‐homogeneous Markov chain model. Furthermore, cost objectives are employed using the goal‐programming approach, under different operating assumptions, in order to minimize the operational cost in the presence of system's constraints and regulations. Copyright © 2002 John Wiley & Sons, Ltd.     

枚举法在制定生产计划中的应用

赵学慧，赵瑛．枚举法在制定生产计划中的应用，数理统计与管理，１９９７，１６（１），１６～１８．本文通过用枚举法制定生产计划的实例，向管理人员介绍计算线性规划最优解的一种简单而易行的方法     

Maritime crude oil transportation - A split pickup and split delivery problem

The maritime oil tanker routing and scheduling problem is known to the literature since before 1950. In the presented problem, oil tankers transport crude oil from supply points to demand locations around the globe. The objective is to find ship routes, load sizes, as well as port arrival and departure times, in a way that minimizes transportation costs. We introduce a path flow model where paths are ship routes. Continuous variables distribute the cargo between the different routes. Multiple products are transported by a heterogeneous fleet of tankers. Pickup and delivery requirements are not paired to cargos beforehand and arbitrary split of amounts is allowed. Small realistic test instances can be solved with route pre-generation for this model. The results indicate possible simplifications and stimulate further research.     

A task and resource scheduling system for automated planning

Planning is done at both the strategic and tactical levels. This paper classifies some previous planning techniques into these different levels, and details of some of their problems. A planning technique known as heuristic task scheduling is then presented along with a planner architecture that integrates task-scheduling with more traditional techniques to form a system that bridges the strategic/tactical division     

A genetic approach for strategic resource allocation planning

Enterprises often implement a measurement system to monitor their march towards their strategic goals. Although this way it is possible to assess the progress of each goal, there is no structured way to reconsider resource allocation to those goals and to plan an optimal (or near optimal) allocation scheme. In this study we propose a genetic approach to match each goal with an autonomous entity (agent) with a specific resource sharing behavior. The overall performance is evaluated through a set of functions and genetic algorithms are used to eventuate in approximate optimal behavior’s schemes. To outline the strategic goals of the enterprise we used the balanced scorecard method. Letting agents deploy their sharing behavior over simulation time, we measure the scorecard’s performance and detect distinguished behaviors, namely recommendations for resource allocation.