A DYNAMIC PROGRAMMING MODEL FOR OPTIMAL ALLOCATION OF DECISION TIME

Recurrent decision making by a lower-level manager can be viewed as a sequential decision process in which time and uncertainty are limiting factors. Under these conditions, the manager must determine how to best utilize his decision making time consistent with his own particular set of decision values. A dynamic programming model was devised to determine the optimal (consistent) allocation of decision time among five different types of problems for a sequence of simulated recurrent decision situations. Fifty-one lower-level managers were interviewed about their use of decision time and decision procedures. The model was validated by comparing model assumptions and results with the findings from the interviews. The model was used to determine the effects of variations in the levels of time available and uncertainty upon the optimal allocation of decision time.     

Evaluation of hazard brochures using topic viewing durations: Application to tsunami evacuation brochures

This study describes a novel method of assessing risk communication effectiveness by reporting an evaluation of a tsunami information brochure by 90 residents of three Pacific coast communities that are vulnerable to a Cascadia Subduction Zone earthquake and tsunami—Commencement Bay, Washington; Lincoln City, Oregon; and Eureka, California. Study participants viewed information that was presented in DynaSearch, an internet-based computer system that allowed them to view text boxes and tsunami inundation zone maps. DynaSearch recorded the number of times each text box or map was clicked and the length of time that it was viewed. This information viewing phase was followed by questionnaire pages assessing important aspects of tsunami hazard and sources of tsunami warnings. Participants gave the longest click durations to what to do in the emergency period during earthquake shaking and in its immediate aftermath before a tsunami arrives—topics that should be displayed prominently in tsunami brochures and emphasized in talks to community groups. The smallest adjusted click durations were associated with advance preparations for a tsunami—topics that can be posted on websites whose URLs are printed in the brochures.     

具有优先约束和加工时间依赖开工时间的单机排序问题

研究工件间的优先约束为串并有向图的单机加权总完工时间问题,通过证明在工件加工时间是开工时间的线性函数的情况下,模块M的ρ因子最大初始集合I中的工件优先于模块M中的其它工件加工,并且被连续加工所得的排序为最优排序,从而将Lawler用来求解约束为串并有向图的单机加权总完工时间问题的方法推广到这个问题上来。     

UNEMPLOYMENT INSURANCE IN WELFARE STATES: THE IMPACTS OF SOFT DURATION CONSTRAINTS

Abstract Based on a major reform of Norwegian unemployment insurance (UI), we examine the behavioral impacts of soft and hard UI duration constraints. A constraint is interpreted as hard if a claimant cannot rely on any form of income support after exhaustion, and as soft if UI is replaced by follow‐on benefits or participation in active labor market programs (ALMP). We find that both hard and soft constraints raise the job hazard significantly, with surprisingly similar spikes at UI exhaustion. Participation in ALMP raises the probability of eventually finding a job, but at the cost of lengthening the overall job‐search period.     

Family members' experiences with viewing in the wake of sudden death

Sudden deaths leave families in crisis and interacting with many professionals from notification through to burial. Whether to view the deceased is often central to discussion. Practice guidelines have evolved over time regarding where, when, how, and why viewing should or should not occur. Unfortunately, there is much contradiction in existing recommendations and a marked absence of a supporting evidence base for the practice of viewing itself, and the influence of this practice on the overall bereavement process. Using a qualitative approach, this study explored the perspectives and experiences of the suddenly bereaved with respect to: viewing or not having viewed; whether or not their viewing experiences have impacted on their bereavement process; and explored particular aspects of their experience such as interactions with various professionals. Results of this study are clustered and presented under three core themes: viewing specifics; intrapersonal responses; and professional interactions.     

强制性约束下企业信息安全投资与网络保险的最优决策分析

研究了强制性约束下企业信息安全投资和网络保险的最优决策问题,对比了可观测企业损失和不可观测企业损失两种情形下基于破产概率约束的最优安全投资和网络保险保费厘定。研究结果表明：在可观测损失和公平保费情况下,当最大化单个企业的期望效用时,存在最优安全投资额,并且政府补贴和强制性约束都可以激励企业增加安全投资;但是当最大化所有企业效用时,只有强制性约束才能增加企业安全投资使得总效用最大化,并且企业的最优安全投资与损失的可观测程度无关。在不可观测损失情况下,当最大化单个企业期望效用时,企业的安全投资增大,而最大化所有企业效用时,存在正网络外部性,即任何企业均不敢轻易的减少安全投资,即使同在一个网络中的其他企业减少了安全投资。此外,在破产概率约束下,随着保费的增加,当损失可观测时,企业的安全投资也增加,但期望效用减少了;而当损失不可观测时,企业的安全投资和期望效用均减少。本文所得结论对政府设定强制性标准,以及企业利用安全投资和网络保险进行信息安全风险控制具有较好的参考价值。     

提前期、构建成本和短缺量拖后率均可控的EOQ模型

传统库存模型通常将提前期和构建成本视为不可控制。事实上可以通过追加投资缩短提前期和降低构建成本。缺货期间,为减少订单丢失量和补偿顾客的损失,供应商会给予一定的价格折扣。现实库存系统中,容易得到需求的期望值和标准差,但较难得到其分布规律。基于此,考虑短缺量拖后率与价格折扣和缺货期间库存水平相关,提出了一种需求为任意分布且提前期和构建成本均可控的EOQ模型,证明了模型存在唯一最优解,给出了一种寻优算法。数值仿真分析表明,一般情况下,压缩提前期和降低构建成本能降低订购批量和安全库存,降低库存总成本;短缺量拖后系数和缺货概率对库存总成本影响较大,企业应尽量降低缺货概率,尤其在短缺量拖后系数较小时。     

带预算约束的广告主均衡报价研究——基于纳什均衡角度

从广告主角度出发，研究基于纳什均衡概念的带有预算约束的关键词拍卖问题。首先推导出纳什均衡下各个广告主报价的上界和下界。其次给出广告主报价向上偏离无利可图的充要条件，并进行了数值分析。此外，通过数值实例分析了广告主报价向下偏离时对其收益的影响。利用各个广告主报价的上下界和预算刻画了带有预算约束的纳什均衡。最后，利用广告主报价在纳什均衡下的上界给出报价向量是带预算约束的纳什均衡的充要条件。对于广告主制定预算策略具有参考作用。     

A stochastic programming model for production planning of perishable products with postponement

This study addresses the production planning problem for perishable products, in which the cost and shortage of products are minimised subject to a set of constraints such as warehouse space, labour working time and machine time. Using the concept of postponement, the production process for perishable products is differentiated into two phases to better utilise the resources. A two-stage stochastic programming with recourse model is developed to determine the production loading plan with uncertain demand and parameters. A set of data from a toy company shows the benefits of the postponement strategy: these include lower total cost and higher utilisation of resources. The impact of unit shortage cost under different probability distribution of economic scenarios on the total cost is analyzed. Comparative analysis of solutions with and without postponement strategies is also performed.     

The falling tide algorithm: A new multi-objective approach for complex workforce scheduling

We present a hybrid approach of goal programming and meta-heuristic search to find compromise solutions for a difficult employee scheduling problem, i.e. nurse rostering with many hard and soft constraints. By employing a goal programming model with different parameter settings in its objective function, we can easily obtain a coarse solution where only the system constraints (i.e. hard constraints) are satisfied and an ideal objective-value vector where each single goal (i.e. each soft constraint) reaches its optimal value. The coarse solution is generally unusable in practise, but it can act as an initial point for the subsequent meta-heuristic search to speed up the convergence. Also, the ideal objective-value vector is, of course, usually unachievable, but it can help a multi-criteria search method (i.e. compromise programming) to evaluate the fitness of obtained solutions more efficiently. By incorporating three distance metrics with changing weight vectors, we propose a new time-predefined meta-heuristic approach, which we call the falling tide algorithm, and apply it under a multi-objective framework to find various compromise solutions. By this approach, not only can we achieve a trade off between the computational time and the solution quality, but also we can achieve a trade off between the conflicting objectives to enable better decision-making.     

Integrated Order Scheduling and Packing

We consider an integrated production–distribution scheduling model in a make‐to‐order supply chain consisting of one supplier and one customer. The supplier receives a set of orders from the customer at the beginning of a planning horizon. The supplier needs to process all the orders at a single production line, pack the completed orders to form delivery batches, and deliver the batches to the customer. Each order has a weight, and the total weight of the orders packed in a batch must not exceed the capacity of the delivery batch. Each delivery batch incurs a fixed distribution cost. The problem is to find jointly a schedule for order processing and a way of packing completed orders to form delivery batches such that the total distribution cost (or equivalently, the number of delivery batches) is minimized subject to the constraint that a given customer service level is guaranteed. We consider two customer service constraints—meeting the given deadlines of the orders; or requiring the average delivery lead time of the orders to be within a given threshold. Several problems of the model with each of those constraints are considered. We clarify the complexity of each problem and develop fast heuristics for the NP‐hard problems and analyze their worst‐case performance bounds. Our computational results indicate that all the heuristics are capable of generating near optimal solutions quickly for the respective problems.     

Physicians’ Labour Supply: The Wage Impact on Hours and Practice Combinations

Abstract. It is a stated aim to improve physician services in underserved sectors and areas. Increased wages is one instrument for boosting the hours provided by the personnel to the prioritized sub‐markets. This study applies an econometric framework that allows for non‐convex budget sets, non‐linear labour supply curves and imperfect markets with institutional constraints. The labour supply decision is viewed as a choice from a set of discrete alternatives (job packages) in a structural labour supply model estimated on Norwegian micro data. An out‐of‐sample prediction is also presented and evaluated by means of a natural experiment.     

BAB算法中集成CPT求解job-shop调度问题

CSP(constraintsatisfactoryproblem)的优势在于能够处理复杂约束,获得一个满足约束的解,但难以保证解的质量.OR(operationresearch)的优点是获得最优解或近优解,但它求解复杂约束的优化问题非常困难.CPT(constraintpropagationtechnique)是CSP的主要搜索技术,BAB(branch_and_bound)是OR常用的优化算法.提出了一种将CPT集成于BAB中的混合算法,从一个新的角度解决具有一般性与挑战性的job shop调度问题.其主要特点是,通过在BAB算法中嵌入动态可调的时间窗口约束和加强一致性CPT搜索方法,融合BAB的优化能力和CPT处理复杂约束的能力,提高BAB的优化性能及实际应用能力.实验结果令人满意,证明了算法的有效性.     

考虑通行约束和运力限制的灾后应急物资联合调度优化研究

考虑到灾后路网受损难以运输应急物资，本文研究了应急响应中车辆-直升机联合调度的路径优化问题。针对受灾地区的实时路况，通往灾区的救援工具受到数量以及装载量的约束，本文将受灾点等待救援的平均时间最短以及应急网络总费用最低设为目标，构建运力受限条件下带通行约束的救援物资联合运输多目标优化模型，然后根据随机邻域搜索变异和分级交叉的思想构建出一种带精英策略的非支配排序混合进化算法（NSHEA-II）得到模型的解，并利用算例分析对该算法进行可行性检验。结果发现，本文构建的NSHEA-II算法相对NSGA-II算法能够得到较好的结果且波动性较小，这为决策者制定救援物资的配送方案提供有效的技术支撑。     

Decision Making for Risk Management: A Comparison of Graphical Methods for Presenting Quantitative Uncertainty

Previous research has shown that people err when making decisions aided by probability information. Surprisingly, there has been little exploration into the accuracy of decisions made based on many commonly used probabilistic display methods. Two experiments examined the ability of a comprehensive set of such methods to effectively communicate critical information to a decision maker and influence confidence in decision making. The second experiment investigated the performance of these methods under time pressure, a situational factor known to exacerbate judgmental errors. Ten commonly used graphical display methods were randomly assigned to participants. Across eight scenarios in which a probabilistic outcome was described, participants were asked questions regarding graph interpretation (e.g., mean) and made behavioral choices (i.e., act; do not act) based on the provided information indicated that decision‐maker accuracy differed by graphical method; error bars and boxplots led to greatest mean estimation and behavioral choice accuracy whereas complementary cumulative probability distribution functions were associated with the highest probability estimation accuracy. Under time pressure, participant performance decreased when making behavioral choices.     

Hybridization of tabu search with feasible and infeasible local searches for periodic home health care logistics

This paper addresses a periodic vehicle routing problem encountered in home health care (HHC) logistics. It extends the classical Periodic Vehicle Routing Problem with Time Windows (PVRPTW) to three types of demands of patients at home. Demands include transportation of drugs/medical devices between the HHC depot and patients׳ homes, delivery of special drugs from the hospital to patients, and delivery of blood samples from patients to the lab. Each patient requires a certain number of visits within a planning horizon and has a set of possible combinations of visit days. Daily routing should meet time window constraints associated with patients, the hospital and the lab. The problem consists in determining the visit days of each patient and vehicle routes for each day in order to minimize the maximal routing costs among all routes over the horizon. We propose a Tabu Search method combined with different local search schemes including both feasible and infeasible local searches. The proposed approaches are tested on a range of instances derived from existing Vehicle Routing Problem with Time Window (VRPTW) benchmarks and benchmarks on special cases of our problem. Numerical results show that local search scheme starting with an infeasible local search with a small probability followed by a feasible local search with high probability is an interesting hybridization. Experiments with field data from a HHC company show that the proposed approach reduces the total cost and better balances the workloads of vehicles.     

Implicit cover inequalities

In this paper we consider combinatorial optimization problems whose feasible sets are simultaneously restricted by a binary knapsack constraint and a cardinality constraint imposing the exact number of selected variables. In particular, such sets arise when the feasible set corresponds to the bases of a matroid with a side knapsack constraint, for instance the weighted spanning tree problem and the multiple choice knapsack problem. We introduce the family of implicit cover inequalities which generalize the well-known cover inequalities for such feasible sets and discuss the lifting of the implicit cover inequalities. A computational study for the weighted spanning tree problem is reported.     

基于拍卖机制的资源转移时间型动态分布式多项目调度

实践中,企业并行实施地域上分散的多个项目时,资源在各子项目之间的转移时间是影响多项目整体进度的关键因素,同时在动态多项目环境下,新项目不断到达且到达时间不可预知使得制定多项目调度计划遭遇更大困难。本文在动态环境下对资源转移时间型分布式多项目调度问题进行建模和求解,基于多代理系统建立分布式多项目调度问题的动态模型,并将拍卖理论引入其中,设计一种基于时间窗拍卖机制的分布式多代理系统(DMAS/ATW),在动态环境和资源转移时间约束下为多项目配置全局资源。通过一个具体的分布式多项目示例详细分析DMAS/ATW算法的动态调度过程,并基于MPSPLIB中的分布式多项目算例开展数值实验。实验结果表明：无资源转移时间约束时,DMAS/ATW算法求得的平均项目延迟同比相关文献中的DMAS/RIA算法最多减少42%,平均减少26%;有资源转移时间约束时,DMAS/ATW算法对1/3算例集的求解结果优于DMAS/RIA算法在无资源转移时间约束时的结果,验证了本文DMAS/ATW算法求解效果的优异性。对算例规模和全局资源利用系数的实验分析还表明,DMAS/ATW算法对不同规模和资源约束紧张程度的算例都具有良好的适应性。     

A certifying algorithm for lattice point feasibility in a system of UTVPI constraints

This paper is concerned with the design and analysis of a certifying algorithm for checking the lattice point feasibility of a class of constraints called unit two variable per inequality (UTVPI) constraints. A UTVPI constraint has at most two non-zero variables and the coefficients of the non-zero variables belong to the set \(\{+\,1,\ -\,1\}\). These constraints occur in a number of application domains, including but not limited to program verification, abstract interpretation, and operations research. As per the literature, the fastest known model generating algorithm for checking lattice point feasibility in UTVPI constraint systems runs in \(O(m \cdot n+n^{2} \cdot \log n)\) time and \(O(n^{2})\) space, where m represents the number of constraints and n represents the number of variables in the constraint system (Lahiri and Musuvathi, in: Proceedings of the 5th  international workshop on the frontiers of combining systems (FroCos), lecture notes in computer science, vol 3717, pp 168–183, 2005). In this paper, we design and analyze a new algorithm for checking the lattice point feasibility of UTVPI constraints. The presented algorithm runs in \(O(m \cdot n)\) time and \(O(m+n)\) space. Additionally it is certifying in that it produces a satisfying assignment in the event that it is presented with feasible instances and refutations in the event that it is presented with infeasible instances. The importance of providing certificates cannot be overemphasized, especially in mission-critical applications. Our approaches for the lattice point feasibility problem in UTVPI constraint systems is fundamentally different from existing approaches for this problem; indeed, it is based on new insights into combining well-known inference rules for these systems.     

Product Assortment and Price Competition under Multinomial Logit Demand

The role of assortment planning and pricing in shaping sales and profits of retailers is well documented and studied in monopolistic settings. However, such a role remains relatively unexplored in competitive environments. In this study, we study equilibrium behavior of competing retailers in two settings: (i) when prices are exogenously fixed, and retailers compete in assortments only; and (ii) when retailers compete jointly in assortment and prices. For this, we model consumer choice using a multinomial Logit, and assume that each retailer selects products from a predefined set, and faces a display constraint. We show that when the sets of products available to retailers do not overlap, there always exists one equilibrium that Pareto‐dominates all others, and that such an outcome can be reached through an iterative process of best responses. A direct corollary of our results is that competition leads a firm to offer a broader set of products compared to when it is operating as a monopolist, and to broader offerings in the market compared to a centralized planner. When some products are available to all retailers, that is, assortments might overlap, we show that display constraints drive equilibrium existence properties.