Exploiting self‐canceling demand point aggregation error for some planar rectilinear median location problems

When solving location problems in practice it is quite common to aggregate demand points into centroids. Solving a location problem with aggregated demand data is computationally easier, but the aggregation process introduces error. We develop theory and algorithms for certain types of centroid aggregations for rectilinear 1‐median problems. The objective is to construct an aggregation that minimizes the maximum aggregation error. We focus on row‐column aggregations, and make use of aggregation results for 1‐median problems on the line to do aggregation for 1‐median problems in the plane. The aggregations developed for the 1‐median problem are then used to construct approximate n‐median problems. We test the theory computationally on n‐median problems (n ≥ 1) using both randomly generated, as well as real, data. Every error measure we consider can be well approximated by some power function in the number of aggregate demand points. Each such function exhibits decreasing returns to scale. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 614–637, 2003.     

不同流量的复杂保障网络抗毁性仿真分析

通过引入流量强度指数和流量分布指数,建立了不同网络流量下的复杂保障网络级联失效抗毁性模型。基于该模型比较分析了无标度网络、随机网络和复杂保障网络在不同流量强度和流量分布下对单个节点的随机失效和故意攻击的抗毁性。结果表明:复杂保障网络的抗毁性随着流量强度的增加急剧下降。此外,流量分布对复杂保障网络的抗毁性也有显著影响。     

基于GAHP的作战决策方案优选模型

优选科学合理的作战方案,是指挥员作战决策的关键。根据作战实际情况,运用五标度和六标度法量化了各因素对作战决策方案的影响指标,建立了基于多人层次分析法(GAHP)理论的优选作战决策方案数学模型,以从方案中选出作战效益最好、付出代价最小且最具可行性的方案,作为决策的具体行动依据。最后通过实例验证了模型的可操作性。GAHP方法能很好地运用不同决策者对方案的不同评价,形成最终决策,对作战指挥决策有一定的现实意义。     

舰船空调系统不同保障模式的效费分析

分析了舰船全寿命期和使用期的结构,在此基础上,借助于WSEIAC模型,分别对舰船空调系统在两种保障方式的全寿命使用期效能和费用的各个指标进行了建模,提出了指标计算的思路与计算方法.结合海军舰船特点,在对WSEIAC效能模型进行修改和完善的基础上,给出了计算示例,结果显示了海军舰船空调系统采用岸基保障方式的合理性和优越性.     

模糊理论与D-S理论在指控系统目标识别融合中的应用

多传感器信息融合技术已获得了普遍的关注和广泛的应用,其理论和方法已成为智能信息处理的一个重要领域,模糊理论与证据理论(D-S)是主要的技术之一.在某试飞指控系统中,为了获得可靠的识别结果需要目标识别的融合问题.系统的从实际出发提出了基于模糊理论与D-S理论的目标识别融合方法.仿真计算结果表明,该模型和方法具有方法简单、运算量小和识别结果可靠等优点,具有一定的理论意义和使用价值.     

Production planning with resources subject to congestion

A fundamental difficulty in developing effective production planning models has been accurately reflecting the nonlinear dependency between workload and lead times. We develop a mathematical programming model for production planning in multiproduct, single stage systems that captures the nonlinear dependency between workload and lead times. We then use outer linearization of this nonlinear model to obtain a linear programming formulation and extend it to multistage systems. Extensive computational experiments validate the approach and compare its results to conventional models that assume workload‐independent planning lead times. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009     

A model to design recreational boat mooring fields

This article develops a mathematical model and heuristic algorithm to design recreational boating mooring fields. The boating industry is important to the Florida economy, and boat storage is becoming a concern among those in the industry. The mooring field design problem is formulated to maximize the total number of boat feet moored in the mooring field. In the model, we allow two adjacent moorings to overlap, which introduces a risk that under certain conditions the boats on these moorings could contact each other. We identify the conditions when contact is possible and quantify the probability of contact. The mooring field design problem is formulated as a nonlinear mixed‐integer programming problem. To solve the problem, we decompose it into two separate models, a mooring radii assignment model and a mooring layout model, which are solved sequentially. The first is solved via exhaustive enumeration and the second via a depth‐first search algorithm. Two actual mooring fields are evaluated, and in both cases our model leads to better layouts than ones experts developed manually. The mooring field design model rationalizes the mooring field design and shows that in one case by increasing the risk from 0 to 1%, the mooring efficiency increases from 74.8% to 96.2%. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009     

Technical note: A computationally efficient algorithm for undiscounted Markov decision processes with restricted observations

We present a computationally efficient procedure to determine control policies for an infinite horizon Markov Decision process with restricted observations. The optimal policy for the system with restricted observations is a function of the observation process and not the unobservable states of the system. Thus, the policy is stationary with respect to the partitioned state space. The algorithm we propose addresses the undiscounted average cost case. The algorithm combines a local search with a modified version of Howard's (Dynamic programming and Markov processes, MIT Press, Cambridge, MA, 1960) policy iteration method. We demonstrate empirically that the algorithm finds the optimal deterministic policy for over 96% of the problem instances generated. For large scale problem instances, we demonstrate that the average cost associated with the local optimal policy is lower than the average cost associated with an integer rounded policy produced by the algorithm of Serin and Kulkarni Math Methods Oper Res 61 (2005) 311–328. © 2008 Wiley Periodicals, Inc. Naval Research Logistics 2009     

A multifaceted heuristic for the orienteering problem

The orienteering problem involves the selection of a path between an origin and a destination which maximizes total score subject to a time restriction. In previous work we presented an effective heuristic for this NP-hard problem that outperformed other heuristics from the literature. In this article we describe and test a significantly improved procedure. The new procedure is based on four concepts—center of gravity, randomness, subgravity, and learning. These concepts combine to yield a procedure which is much faster and which results in more nearly optimal solutions than previous procedures.