具有竞争关系的多参与人委托代理问题研究

针对多委托人一多代理人委托代理问题,本文在多委托人之间和多代理人之间均存在竞争关系情形下,建立了非对称信息委托代理模型.分析表明,代理人努力水平对其产出的作用越敏感,代理人和委托人都越愿意付出更多努力;当委托人业务能力高低对代理人的影响较敏感时,委托人更愿意花心思去提高业务能力;委托一代理关系中的任何一方竞争过于激烈时会被处于委托一代理关系中的另一方利用.     

A Bayesian approach to continuous type principal-agent problems

Singham (2019) proposed an important advance in the numerical solution of continuous type principal-agent problems using Monte Carlo simulations from the distribution of agent “types” followed by bootstrapping. In this paper, we propose a Bayesian approach to the problem which produces nearly the same results without the need to rely on optimization or lower and upper bounds for the optimal value of the objective function. Specifically, we cast the problem in terms of maximizing the posterior expectation with respect to a suitable posterior measure. In turn, we use efficient Markov Chain Monte Carlo techniques to perform the computations.     

An automatic algorithm selection approach for the multi-mode resource-constrained project scheduling problem

This paper investigates the construction of an automatic algorithm selection tool for the multi-mode resource-constrained project scheduling problem (MRCPSP). The research described relies on the notion of empirical hardness models. These models map problem instance features onto the performance of an algorithm. Using such models, the performance of a set of algorithms can be predicted. Based on these predictions, one can automatically select the algorithm that is expected to perform best given the available computing resources. The idea is to combine different algorithms in a super-algorithm that performs better than any of the components individually. We apply this strategy to the classic problem of project scheduling with multiple execution modes. We show that we can indeed significantly improve on the performance of state-of-the-art algorithms when evaluated on a set of unseen instances. This becomes important when lots of instances have to be solved consecutively. Many state-of-the-art algorithms perform very well on a majority of benchmark instances, while performing worse on a smaller set of instances. The performance of one algorithm can be very different on a set of instances while another algorithm sees no difference in performance at all. Knowing in advance, without using scarce computational resources, which algorithm to run on a certain problem instance, can significantly improve the total overall performance.     

Characterizing optimal wages in principal-agent problems without using the first-order approach

The analysis of the principal-agent problem usually requires the classical first-order approach (FOA). However, the validity of the FOA makes restrictive assumptions on the problem under consideration such as the convexity of the distribution function condition. The main aim of this paper is to compute the optimal wages and characterize a closed form solution to the risk-neutral principal-agent problem with limited liability constraints. The development in this paper mainly invokes certain techniques in the semi-infinite programming rather than the FOA.     

On a thermoelastic material having a dipolar structure and microtemperatures

In this study we formulate the mixed initial boundary value problem for a dipolar thermoelastic material whose micro-particles possess microtemperatures. Then this mixed problem is transformed in a Cauchy problem attached to a temporally equation of evolution on a specific Hilbert space, which will be suitably chosen. As such, we will be able to use certain results specific to the theory of the semigroups of contractions in order to obtain the existence and uniqueness of the solution for our problem. The theory of semigroups also facilitates our approach regarding the continuous dependence of the solution upon initial data and loads. Finally, we reduce our model to the isotropic case and perform numerical simulations for the corresponding system of partial differential equations by means of the finite element method.     

Augmented nodal matrices and normal trees

Augmented nodal matrices play an important role in the analysis of different features of electrical circuit models. Their study can be addressed in an abstract setting involving two- and three-colour weighted digraphs. By means of a detailed characterization of the structure of proper and normal trees, we provide a unifying framework for the rank analysis of augmented matrices. This covers in particular Maxwell’s tree-based determinantal expansions of (non-augmented) nodal matrices, which can be considered as a one-colour version of our results. Via different colour assignments to circuit devices, we tackle the DC-solvability problem and the index characterization of certain differential-algebraic models which arise in the nodal analysis of electrical circuits, extending several known results of passive circuits to the non-passive context.     

A solution approach for dynamic vehicle and crew scheduling

In this paper, we discuss the dynamic vehicle and crew scheduling problem and we propose a solution approach consisting of solving a sequence of optimization problems. Furthermore, we explain why it is useful to consider such a dynamic approach and compare it with a static one. Moreover, we perform a sensitivity analysis on our main assumption that the travel times of the trips are known exactly a certain amount of time before actual operation.We provide extensive computational results on some real-world data instances of a large public transport company in the Netherlands. Due to the complexity of the vehicle and crew scheduling problem, we solve only small and medium-sized instances with such a dynamic approach. We show that the results are good in the case of a single depot. However, in the multiple-depot case, the dynamic approach does not perform so well. We investigate why this is the case and conclude that the fact that the instance has to be split in several smaller ones, has a negative effect on the performance.     

On large Eddy simulation and variational multiscale methods in the numerical simulation of turbulent incompressible flows

Numerical simulation of turbulent flows is one of the great challenges in Computational Fluid Dynamics (CFD). In general, Direct Numerical Simulation (DNS) is not feasible due to limited computer resources (performance and memory), and the use of a turbulence model becomes necessary. The paper will discuss several aspects of two approaches of turbulent modeling—Large Eddy Simulation (LES) and Variational Multiscale (VMS) models. Topics which will be addressed are the detailed derivation of these models, the analysis of commutation errors in LES models as well as other results from mathematical analysis.     

Models and algorithms for a staff scheduling problem

We present mathematical models and solution algorithms for a family of staff scheduling problems arising in real life applications. In these problems, the daily assignments to be performed are given and the durations (in days) of the working and rest periods for each employee in the planning horizon are specified in advance, whereas the sequence in which these working and rest periods occur, as well as the daily assignment for each working period, have to be determined. The main objective is the minimization of the number of employees needed to perform all daily assignments in the horizon. We decompose the problem into two steps: the definition of the sequence of working and rest periods (called pattern) for each employee, and the definition of the daily assignment to be performed in each working period by each employee. The first step is formulated as a covering problem for which we present alternative ILP models and exact enumerative algorithms based on these models. Practical experience shows that the best approach is based on the model in which variables are associated with feasible patterns and generated either by dynamic programming or by solving another ILP. The second step is stated as a feasibility problem solved heuristically through a sequence of transportation problems. Although in general this procedure may not find a solution (even if one exists), we present sufficient conditions under which our approach is guaranteed to succeed. We also propose an iterative heuristic algorithm to handle the case in which no feasible solution is found in the second step. We present computational results on real life instances associated with an emergency call center. The proposed approach is able to determine the optimal solution of instances involving up to several hundred employees and a working period of up to 6 months. Mathematics Subject Classification (2000): 90B70, 90C10, 90C27, 90C39, 90C57, 90C59     

Facets and algorithms for capacitated lot sizing

The dynamic economic lot sizing model, which lies at the core of numerous production planning applications, is one of the most highly studied models in all of operations research. And yet, capacitated multi-item versions of this problem remain computationally elusive. We study the polyhedral structure of an integer programming formulation of a single-item capacitated version of this problem, and use these results to develop solution methods for multi-item applications. In particular, we introduce a set of valid inequalities for the problem and show that they define facets of the underlying integer programming polyhedron. Computational results on several single and multiple product examples show that these inequalities can be used quite effectively to develop an efficient cutting plane/branch and bound procedure. Moreover, our results show that in many instances adding certain of these inequalities a priori to the problem formulation, and avoiding the generation of cutting planes, can be equally effective.Supported by Grant #ECS-8316224 from the Systems Theory and Operations Research Program of the National Science Foundation.     

代建制中委托代理的激励、监督与合谋防范

在推行代建制的过程中,信息的不对称不可避免,易引发道德风险,因而在当前相关法规和信用机制都不健全的情况下,如何有效保证政府投资人的利益备受关注.针对该问题,基于委托-代理理论和优化理论,突破传统的单变量建模方法,将严格监管、有效激励与合谋防范纳入政府代建项目管理的框架,分别建立了以努力变量为多维变量的激励合同和监管模型,以及项目管理公司与承包商之间的合谋防范模型.最终建立了由政府投资人、项目管理公司及承包商等三大主体组成代建制的委托代理体系.     

Reducibility of minimax to minisum 0–1 programming problems

We consider 0–1 programming problems with a minimax objective function and any set of constraints. Upon appropriate transformations of its cost coefficients, such a minimax problem can be reduced to a linear minisum problem with the same set of feasible solutions such that an optimal solution to the latter will also solve the original minimax problem.Although this reducibility applies for any 0–1 programming problem, it is of particular interest for certain locational decision models. Among the obvious implications are that an algorithm for solving a p-median (minisum) problem in a network will also solve a corresponding p-center (minimax) problem.It should be emphasized that the results presented will in general only hold for 0–1 problems due to intrinsic properties of the minimax criterion.     

Hybrid genetic algorithms for bin-packing and related problems

The genetic algorithm (GA) paradigm has attracted considerable attention as a promising heuristic approach for solving optimization problems. Much of the development has related to problems of optimizing functions of continuous variables, but recently there have been several applications to problems of a combinatorial nature. What is often found is that GAs have fairly poor performance for combinatorial problems if implemented in a naive way, and most reported work has involved somewhat ad hoc adjustments to the basic method. In this paper, we will describe a general approach which promises good performance for a fairly extensive class of problems by hybridizing the GA with existing simple heuristics. The procedure will be illustrated mainly in relation to the problem ofbin-packing, but it could be extended to other problems such asgraph partitioning, parallel-machine scheduling andgeneralized assignment. The method is further extended by usingproblem size reduction hybrids. Some results of numerical experiments will be presented which attempt to identify those circumstances in which these heuristics will perform well relative to exact methods. Finally, we discuss some general issues involving hybridization: in particular, we raise the possibility of blending GAs with orthodox mathematical programming procedures.     

Hub-and-spoke network design and fleet deployment for string planning of liner shipping

All shipping liner companies divide their service regions into several rotations (strings) in order to operate their container vessels. A string is the ordered set of ports at which a container vessel will call. Each port is usually called at no more than twice along one string, although a single port may be called at several times on different strings. The size of string dictates the number of vessels required to offer a given frequency of service. In order to better use their shipping capacity, groups of Liner Service Providers sometimes make a short term agreement to merge some of their service routes (in a certain region) into one main ocean going rotation and p feeder rotations. In order to minimize the weighted sum of transit time, and fixed deployment costs, this paper proposes a mixed integer linear programming model of the network design, and an allocation of proper capacity size and frequency setting for every rotation. Given that none of the existing general-purpose MIP solvers is able to solve even very small problem instances in a reasonable time, we propose a Lagrangian decomposition approach which uses a heuristic procedure and is capable of obtaining practical and high quality solutions in reasonable times. The model will be applied on a real example, and we shall present some of the results obtained by our model which show how it facilitates a better use of assets and a significant reduction in the use of fuel, therefore allowing a more environmentally friendly service.     

Cane Railway Scheduling via Constraint Logic Programming: Labelling Order and Constraints in a Real-Life Application

In Australia, cane transport is the largest unit cost in the manufacturing of raw sugar, making up around 35% of the total manufacturing costs. Producing efficient schedules for the cane railways can result in significant cost savings. This paper presents a study using Constraint Logic Programming (CLP) to solve the cane transport scheduling problem. Tailored heuristic labelling order and constraints strategies are proposed and encouraging results of application to several test problems and one real-life case are presented. The preliminary results demonstrate that CLP can be used as an effective tool for solving the cane transport scheduling problem, with a potential decrease in development costs of the scheduling system. It can also be used as an efficient tool for rescheduling tasks which the existing cane transport scheduling system cannot perform well.     

行业投入产出技术系数与行业获利性波动识别

企业经营环境外部系统因素的不确定性是影响企业所有者与经营者之间委托代理问题解决的主要因素,目前还没有文献系统建立企业经营环境信息的识别方法。本文利用技术效率评价中的理论来研究企业经营环境信息的识别问题。基于(k,y)空间的生产可能集与技术效率发展了描述不同行业投入产出差别的技术系数,给出行业获利性波动的时序识别方法。这些方法对弱化企业所有者与经营者之间信息非对称程度,解决二者之间的委托代理问题提供了一个有效途径。     

“两院制”工程设计审计委托代理博弈分析

为减少业主和设计院之间的信息不对称,本文创新性地构建了一个包括设计院、设计审查院的"两院制"工程设计审计模式。基于委托代理理论对现有设计审计模式和"两院制"设计审计模式进行了博弈分析,给出了这两种模式的最优激励机制。结果发现"两院制"设计审计模式可以减少业主和设计院之间的信息不对称,但只有在审计努力水平达到一定程度后,才能提高业主收益。同时,结果表明信息不对称程度越高、工程风险越大,就越有必要采用"两院制"设计审计模式。     

单体型装配问题及其算法

单核苷酸多态性(SNP)单体型装配问题就是从给定的来自某人染色体的SNP片段中去除错误,重构出尽可能与原来片段一致的单体型.这个问题有几个不同的模型最少片段去除(MFR)问题,最少SNP去除(MSR)问题以及最少错误纠正(MEC)问题.前两个问题的复杂性与算法已有一些学者研究过.第三个问题已被证明是NP完全问题,但这个问题的实际算法还没有.该文对MEC问题给出了一个分支定界算法,这个算法能得到问题的全局最优解.通过这个算法对实际数据的计算说明了MEC模型的合理性,即在一定条件下,通过修正最少的错误重构出的单体型确实是真实的单体型.由于分支定界算法对这样一个NP完全问题不能在可接受的时间内解规模较大的问题,文中又给出了求解MEC问题的两个基于动态聚类的算法,以便对规模较大的问题在可接受的时间内得到近似最优解.数值实际表明这两个算法很快,很有效.这两个算法总能得到与分支定界找到的全局最优解很接近的近似最优解.鉴于MEC问题是NP完全的,这两个算法是有效的、实际的算法.     

Endogenous matching in a market with heterogeneous principals and agents

We employ the assignment game of Shapley and Shubik (Int J Game Theory 1:111–130, 1972) to study the endogenous matching patterns in a market that consists of heterogenous principals and agents. We show that, in general, the equilibrium matching is non-assortative. We then characterize the equilibrium relationship between risk and performance pay and risk and fixed compensation. This is the first paper that characterizes the equilibrium matching, to its fullest possible extent, building on the Holmstrom and Milgrom (Econometrica 55:303–328, 1987) principal-agent model. This model has been used extensively in the empirical literature and therefore we hope that our results will be of value to empirical researchers who wish to study a principal-agent market.     

Phase coexistence in Ising, Potts and percolation models

We study phase coexistence (separation) phenomena in Ising, Potts and random cluster models in dimensions d3 below the critical temperature. The simultaneous occurrence of several phases is typical for systems with appropriately arranged (mixed) boundary conditions or for systems satisfying certain physically natural constraints (canonical ensembles). The various phases emerging in these models define a partition, called the empirical phase partition, of the space. Our main results are large deviations principles for (the shape of) the empirical phase partition. More specifically, we establish a general large deviation principle for the partition induced by large (macroscopic) clusters in the Fortuin–Kasteleyn model and transfer it to the Ising–Potts model where we obtain a large deviation principle for the empirical phase partition induced by the various phases. The rate function turns out to be the total surface free energy (associated with the surface tension of the model and with boundary conditions) which can be naturally assigned to each reasonable partition. These LDP-s imply a weak law of large numbers: asymptotically, the law of the phase partition is determined by an appropriate variational problem. More precisely, the empirical phase partition will be close to some partition which is compatible with the constraints imposed on the system and which minimizes the total surface free energy. A general compactness argument guarantees the existence of at least one such minimizing partition. Our results are valid for temperatures T below a limit of slab-thresholds conjectured to agree with the critical point T_c. Moreover, T should be such that there exists only one translation invariant infinite volume state in the corresponding Fortuin–Kasteleyn model; a property which can fail for at most countably many values and which is conjectured to be true for every T≠T_c.