Partial equilibrium in risk‐based production decisions

Characteristically, a small subset of operational problems admit risk neutrality when contingent claims methodology were used in their analysis. That is, for the majority of manufacturing and production problems, operating cash flows are not directly linked to prices of traded assets. However, to the extent that correlations can be estimated, the methodology's applicability to a broader set of operational problems is supported. Our article addresses this issue with the objective of extending the use of contingent claims techniques to a larger set of operational problems. In broad terms, this objective entails a partial equilibrium approach to the problem of valuing uncertain cash flows. To this end, we assume risk aversion and cast our approach within Merton's intertemporal capital asset pricing model. In this context, we formulate a “generic” production valuation model that is framed as an exercise in stochastic optimal control. The model is versatile in its characterization and can easily be adapted to accommodate a wide‐ranging set of risk‐based operational problems where the underlying sources of uncertainty are not traded. To obtain results, the model is recast as a stochastic dynamic program to be solved numerically. The article addresses a number of fundamental issues in the analysis risk based decision problems in operations. First, in the approach provided, decisions are analyzed under a properly defined risk structure. Second, the process of analysis leads to suitably adjusted probability distributions through which, appropriately discounted expectations are derived. Third, through consolidating existing concepts into a standard and adaptable framework, we extend the applicability of contingent claims methodology to a broader set of operational problems. The approach is advantageous as it obviates the need for exogenously specifying utility functions or discount rates.© 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

Optimal path finding in direction,location, and time dependent environments

This article examines optimal path finding problems where cost function and constraints are direction, location, and time dependent. Recent advancements in sensor and data‐processing technology facilitate the collection of detailed real‐time information about the environment surrounding a ground vehicle, an airplane, or a naval vessel. We present a navigation model that makes use of such information. We relax a number of assumptions from existing literature on path‐finding problems and create an accurate, yet tractable, model suitable for implementation for a large class of problems. We present a dynamic programming model which integrates our earlier results for direction‐dependent, time and space homogeneous environment, and consequently, improves its accuracy, efficiency, and run‐time. The proposed path finding model also addresses limited information about the surrounding environment, control‐feasibility of the considered paths, such as sharpest feasible turns a vehicle can make, and computational demands of a time‐dependent environment. To demonstrate the applicability and performance of our path‐finding algorithm, computational experiments for a short‐range ship routing in dynamic wave‐field problem are presented. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

Models and algorithms for shuffling problems in steel plants

In this article, we study item shuffling (IS) problems arising in the logistics system of steel production. An IS problem here is to optimize shuffling operations needed in retrieving a sequence of steel items from a warehouse served by a crane. There are two types of such problems, plate shuffling problems (PSP) and coil shuffling problems (CSP), considering the item shapes. The PSP is modeled as a container storage location assignment problem. For CSP, a novel linear integer programming model is formulated considering the practical stacking and shuffling features. Several valid inequalities are constructed to accelerate the solving of the models. Some properties of optimal solutions of PSP and CSP are also derived. Because of the strong NP‐hardness of the problems, we consider some special cases of them and propose polynomial time algorithms to obtain optimal solutions for these cases. A greedy heuristic is proposed to solve the general problems and its worst‐case performances on both PSP and CSP are analyzed. A tabu search (TS) method with a tabu list of variable length is proposed to further improve the heuristic solutions. Without considering the crane traveling distance, we then construct a rolling variable horizon heuristic for the problems. Numerical experiments show that the proposed heuristic algorithms and the TS method are effective. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

Economic lot sizing with constant capacities and concave inventory costs

This article studies the classical single‐item economic lot‐sizing problem with constant capacities, fixed‐plus‐linear order costs, and concave inventory costs, where backlogging is allowed. We propose an O(T³) optimal algorithm for the problem, which improves upon the O(T⁴) running time of the famous algorithm developed by Florian and Klein (Manage Sci18 (1971) 12–20). Instead of using the standard dynamic programming approach by predetermining the minimal cost for every possible subplan, we develop a backward dynamic programming algorithm to obtain a more efficient implementation. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

基于影响网络与不完全信息多阶段博弈的作战行动序列模型及求解方法

拟制作战计划的关键是生成作战行动序列.考虑作战行动过程中的不确定性以及激烈对抗性,以影响网络分析作战行动和战场态势之间的相互影响,用不完全信息博弈分析敌对双方之间的对抗,建立了基于影响网络和不完全信息多阶段博弈的作战行动序列模型,并给出了求解方法.通过计算实例说明了模型及其求解方法.结果显示该模型生成的COA更适应于对抗环境.     

火力分配环协同度的编队反导决策优化

舰艇编队协同反导决策是一个多阶段多目标的决策系统,依据模糊权距离和隶属度概念,考虑系统中各阶段的协同关系,提出基于火力分配环协同度的概念,将模糊优选理论与动态规划原理有机地结合起来,寻求基于舰艇编队协同反导的多阶段多目标优化的最优均衡策略,并应用于解决舰艇编队协同反导决策的优化中,得出了具有指导意义的结论。     

Bayesian selling problem with partial information

We introduce an optimal stopping problem for selling an asset when the fixed but unknown distribution of successive offers is from one of n possible distributions. The initial probabilities as to which is the true distribution are given and updated in a Bayesian manner as the successive offers are observed. After receiving an offer, the seller has to decide whether to accept the offer or continue to observe the next offer. Each time an offer is observed a fixed cost is incurred. We consider both the cases where recalling a past offer is allowed and where it is not allowed. For each case, a dynamic programming model and some heuristic policies are presented. Using simulation, the performances of the heuristic methods are evaluated and upper bounds on the optimal expected return are obtained. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

Generalized orienteering problem with resource dependent rewards

We introduce a generalized orienteering problem (OP) where, as usual, a vehicle is routed from a prescribed start node, through a directed network, to a prescribed destination node, collecting rewards at each node visited, to maximize the total reward along the path. In our generalization, transit on arcs in the network and reward collection at nodes both consume a variable amount of the same limited resource. We exploit this resource trade‐off through a specialized branch‐and‐bound algorithm that relies on partial path relaxation problems that often yield tight bounds and lead to substantial pruning in the enumeration tree. We present the smuggler search problem (SSP) as an important real‐world application of our generalized OP. Numerical results show that our algorithm applied to the SSP outperforms standard mixed‐integer nonlinear programming solvers for moderate to large problem instances. We demonstrate model enhancements that allow practitioners to represent realistic search planning scenarios by accounting for multiple heterogeneous searchers and complex smuggler motion. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

面向武器装备体系组合规划的集成决策优化框架

针对当前武器装备体系组合规划存在选择空间规模大、决策目标数量多等问题,提出一种集成决策优化框架,用于组合选择和规划武器装备的发展型号、时间和数量。首先对武器装备体系组合规划问题的NP-Hard和高维多目标性质进行定量化分析和公式化描述;然后采用目标规划方法将该问题构建为双目标优化模型;再基于NSGA-II多目标演化计算方法,开发面向本问题的优化算法,求得该模型的Pareto解集合;最后通过TOPSIS方法,从Pareto解集合中求取符合决策者偏好的满意解。通过某侦察预警监视体系发展规划示例,验证了当给定经验数据和决策者偏好信息后,该框架可获得符合要求的武器装备体系组合规划方案,能够支撑武器装备体系发展论证和规划。     

一例多元案例教学法在程序设计课程教学中的应用

通过探讨一例多元案例教学法的教学理念、设计策略、实施方法和过程,解决程序设计课程教学不能点、线、面融合,缺少培养学员设计综合应用程序能力的方法和手段,学员学习目标不明确、缺乏学习兴趣等问题,以有效提高教学效果和质量.