基于关系契约的冷链运营策略博弈分析

针对冷链产品供应链各环节是否严格采取高质量冷链措施的问题,基于供应链成员间的关系契约,运用博弈论方法,构建了冷链供应商和分销商之间的纯战略博弈模型和混合战略博弈模型。通过对Nash均衡的求解分析发现,冷链企业采取高质量冷链措施的概率与冷链企业的冷链成本、监督成本、监督概率、赏罚力度等因素有关。最后,立足于企业长远发展,提出了冷链企业共同提升冷链服务质量的具体建议。     

On the convergence of stationary sequences in topology optimization

We consider structural topology optimization problems including unilateral constraints arising from non‐penetration conditions in contact mechanics. The resulting non‐convex non‐smooth problems are instances of mathematical programs with equilibrium constraints (MPEC), or bi‐level programs. Applying nested (implicit programming) algorithms to this class of problems is problematic owing to the singularity of the feasible set. We propose a perturbation strategy combining the relaxation of the equilibrium constraint with the restriction of the design domain to its regular part only. This strategy allows us to attack the problem numerically using standard non‐linear programming algorithms. We rigorously study the optimality conditions for the original singular problem as well as the convergence of stationary points and globally optimal solutions to approximating problems towards respective stationary points and globally optimal solutions to the original problem. A limited numerical benchmarking of the algorithm is performed. Copyright © 2005 John Wiley & Sons, Ltd.     

网购供应链质量控制的策略研究

针对网购供应链中频繁出现的假冒伪劣等产品质量问题,考虑了由电商平台、平台销售企业和消费者3个理性群体组成的网购供应链,通过构建三方博弈的混合纳什均衡模型,求出了该混合策略纳什均衡解。在此基础上,进一步分析了网购供应链中各因素对相关主体行为概率的影响,得到了各主体的期望收益。运用Matlab R2017a软件对模型影响因素进行了数值仿真分析。研究结果表明,网购供应链质量博弈中存在着混合策略纳什均衡,且各主体的行为概率与惩罚、伪造、检验成本、收益、平台注册费用、后悔值、庆幸值等因素相关。为使各主体的期望收益同时趋于理想状态,电商企业应增加惩罚值和平台注册费用到区间中值,而消费者须增大后悔值、庆幸值到区间最大值。     

Optimal and Heuristic Facility Phase-out Strategies

This paper presents an efficient branch and bound algorithm and near optimal heuristic algorithms for solving the problem of withdrawing inventory and/or service facilities for a good or service whose overall demand is declining over time. In particular, this paper models the problem faced by a manager who must consider closing up to M initially open and operating support facilities as demand shifts and declines over a T period planning horizon. The criterion is minimization of total estimated discounted costs. The costs considered are the variable operating cost at each facility, the transportation costs between facilities and demand centers, and the costs to operate and close each facility. Computational results are presented for both the optimum finding and heuristic algorithms.     

Strategy Selection for Moving Target Defense in Incomplete Information Game

As a core component of the network, web applications have become one of the preferred targets for attackers because the static configuration of web applications simplifies the exploitation of vulnerabilities by attackers. Although the moving target defense (MTD) has been proposed to increase the attack difficulty for the attackers, there is no solo approach can cope with different attacks; in addition, it is impossible to implement all these approaches simultaneously due to the resource limitation. Thus, the selection of an optimal defense strategy based on MTD has become the focus of research. In general, the confrontation of two players in the security domain is viewed as a stochastic game, and the reward matrices are known to both players. However, in a real security confrontation, this scenario represents an incomplete information game. Each player can only observe the actions performed by the opponent, and the observed actions are not completely accurate. To accurately describe the attacker’s reward function to reach the Nash equilibrium, this work simulated and updated the strategy selection distribution of the attacker by observing and investigating the strategy selection history of the attacker. Next, the possible rewards of the attacker in each confrontation via the observation matrix were corrected. On this basis, the Nash-Q learning algorithm with reward quantification was proposed to select the optimal strategy. Moreover, the performances of the Minimax-Q learning algorithm and Naive-Q learning algorithm were compared and analyzed in the MTD environment. Finally, the experimental results showed that the strategy selection algorithm can enable defenders to select a more reasonable defensive strategy and achieve the maximum possible reward.     

基于服务价格和质量承诺的服务商竞争策略研究

现有研究仅关注单一服务商的质量承诺决策,而忽视多个服务商关于服务价格和质量承诺的竞争策略。为弥补这种研究不足,本文的研究并不仅停留在单一的服务承诺研究,而是扩展到服务价格层面进行综合研究,以此探讨服务商竞争策略。本文构建3种竞争模型,并运用最优化方法研究,得到结论如下。1) 在基于服务价格的竞争模型中,当质量承诺水平一定时,一旦有服务商涨价,其他服务商会制定相同的决策。然而,一旦有服务商提高质量承诺水平,其他服务商会制定降价决策予以应对。2) 在基于质量承诺水平的竞争模型中,当服务价格一定时,一旦有服务商提高质量承诺水平,其他服务商会适当地降低质量承诺水平来减少服务失败时的补偿。一旦有服务商从服务价格层面提升竞争力,那么,为应对这种竞争策略,其他服务商就会从质量承诺方面进行补偿。3) 本文基于服务竞争策略研究而建立了竞争模型,从模型研究中发现,各个服务商之间必然存在纳什均衡。本文对服务市场竞争环境下,关于服务价格和质量承诺的竞争策略的制定有一定的实践指导意义。     

Dual-channel supply chain pricing decisions with a risk-averse retailer

This paper investigates a dual-channel supply chain with one risk-neutral manufacturer and one risk-averse retailer where there is only one perishable product with price-dependent stochastic demand. We choose Conditional Value-at-Risk criterion to measure the retailer’s risk-averse level, and assume that the manufacturer’s direct sales channel and the retailer’s traditional channel adopt a consistent pricing strategy. The model explores a Nash bargaining problem where the manufacturer and the retailer negotiate with each other on the wholesale price, the retail price and the order quantity when they have equal bargaining power. It is found that when demand uncertainty follows a uniform distribution, a Nash bargaining equilibrium exists and the retail price will decrease as the retailer becomes more risk averse. However, when the risk-averse indicator increases, the manufacturer’s profit on his direct channel will decrease, increase or first increase and then decrease, depending on the values of the related parameters. The profit shares of the manufacturer and the retailer under the Nash equilibrium model are related to the risk-averse indicator of the retailer. Furthermore, we perform three sets of numerical experiments to verify the effects of the retailer’s risk-averse indicator on decision-making and profit allocations under the different environmental parameters and gain several meaningful managerial insights.     

Non-Cooperative Game of Coordinated Scheduling of Parallel Machine Production and Transportation in Shared Manufacturing

Given the challenges of manufacturing resource sharing and competition in the modern manufacturing industry, the coordinated scheduling problem of parallel machine production and transportation is investigated. The problem takes into account the coordination of production and transportation before production as well as the disparities in machine spatial position and performance. A non-cooperative game model is established, considering the competition and self-interest behavior of jobs from different customers for machine resources. The job from different customers is mapped to the players in the game model, the corresponding optional processing machine and location are mapped to the strategy set, and the makespan of the job is mapped to the payoff. Then the solution of the scheduling model is transformed into the Nash equilibrium of the non-cooperative game model. A Nash equilibrium solution algorithm based on the genetic algorithm (NE-GA) is designed, and the effective solution of approximate Nash equilibrium for the game model is realized. The fitness function, single-point crossover operator, and mutation operator are derived from the non-cooperative game model’s characteristics and the definition of Nash equilibrium. Rules are also designed to avoid the generation of invalid offspring chromosomes. The effectiveness of the proposed algorithm is demonstrated through numerical experiments of various sizes. Compared with other algorithms such as heuristic algorithms (FCFS, SPT, and LPT), the simulated annealing algorithm (SA), and the particle swarm optimization algorithm (PSO), experimental results show that the proposed NE-GA algorithm has obvious performance advantages.     

Incentive compatible resource allocation in concurrent design

This article presents an approach that a manager can use to allocate resources needed to design a system among the members of a concurrent design team. The system being designed is assumed to be composed of a number of subsystems, each designed by a different engineer. These engineers possess private information about the performance of their subsystem as a function of the design resources that they are allocated. This article shows how the manager of such a concurrent design project can induce rational self-interested engineers to reveal truthfully their private subsystem performance functions. This is accomplished through an incentive contract that ties each engineer’s pay to the contribution of their subsystem to the performance of the overall system. The approach builds from a Vickrey–Clarke–Groves mechanism to achieve, as an ex-post Nash equilibrium, truthful reporting of private subsystem performance functions by risk-neutral agents.     

An algorithm for the matrix‐free solution of quasistatic frictional contact problems

A contact enforcement algorithm has been developed for matrix‐free quasistatic finite element techniques. Matrix‐free (iterative) solution algorithms such as non‐linear conjugate gradients (CG) and dynamic relaxation (DR) are desirable for large solid mechanics applications where direct linear equation solving is prohibitively expensive, but in contrast to more traditional Newton–Raphson and quasi‐Newton iteration strategies, the number of iterations required for convergence is typically of the same order as the number of degrees of freedom of the model. It is therefore crucial that each of these iterations be inexpensive to per‐form, which is of course the essence of a matrix free method. In applying such methods to contact problems we emphasize here two requirements: first, that the treatment of the contact should not make an average equilibrium iteration considerably more expensive; and second, that the contact constraints should be imposed in such a way that they do not introduce spurious energy that acts against the iterative solver. These practical concerns are utilized to develop an iterative technique for accurate constraint enforcement that is suitable for non‐linear conjugate gradient and dynamic relaxation iterative schemes. Copyright © 1999 John Wiley & Sons, Ltd.     

Comparison of push and pull control strategies for supply network management in a make-to-stock environment

The performance differences of ‘push’ and ‘pull’ strategies for operational planning and control of a make-to-stock supply network under different environmental conditions (forecast error and initial levels of inventory) were explored. Results suggest that control strategy, forecast error and levels of inventory buffer all significantly affect each of the performance measures studied. Under all combinations of different conditions of inventory buffer level and forecast error, push outperforms pull in terms of customer service level and throughput, while pull outperforms push in term of total inventory. In terms of throughput and customer service level, push is more sensitive to forecast error but less sensitive to levels of inventory buffer than pull.     

供应不确定下制造商的采购策略:回收或双渠道采购

在考虑供应商供应不确定的情形下,构建制造商在不同市场结构下的采购策略选择模型,研究发现:①垄断市场中,当供应不确定性较大时,制造商会选择回收策略;当供应商的不确定性较小时,制造商选择双渠道采购。②竞争市场中对比制造商的均衡利润发现,当供应商供应不确定性大时,两制造商均选择回收策略达到纳什均衡;当供应不确定性处于中间水平时,两制造商选择差异化的采购策略更有利可图;当供应商供应不确定性小时,上游供应商之间的竞争激烈,双渠道采购为市场的均衡策略。此外,还探讨了供应不确定性的变化对制造商的利润影响。     

Two-agent cooperative search using game models with endurance-time constraints

In this article, the problem of two Unmanned Aerial Vehicles (UAVs) cooperatively searching an unknown region is addressed. The search region is discretized into hexagonal cells and each cell is assumed to possess an uncertainty value. The UAVs have to cooperatively search these cells taking limited endurance, sensor and communication range constraints into account. Due to limited endurance, the UAVs need to return to the base station for refuelling and also need to select a base station when multiple base stations are present. This article proposes a route planning algorithm that takes endurance time constraints into account and uses game theoretical strategies to reduce the uncertainty. The route planning algorithm selects only those cells that ensure the agent will return to any one of the available bases. A set of paths are formed using these cells which the game theoretical strategies use to select a path that yields maximum uncertainty reduction. We explore non-cooperative Nash, cooperative and security strategies from game theory to enhance the search effectiveness. Monte-Carlo simulations are carried out which show the superiority of the game theoretical strategies over greedy strategy for different look ahead step length paths. Within the game theoretical strategies, non-cooperative Nash and cooperative strategy perform similarly in an ideal case, but Nash strategy performs better than the cooperative strategy when the perceived information is different. We also propose a heuristic based on partitioning of the search space into sectors to reduce computational overhead without performance degradation.     

On finite-element implementation strategies of Schapery-type constitutive theories

This paper presents two new strategies for implementing Schapery-type nonlinearly viscoelastic constitutive theories into finite element codes. The first strategy uses the original differential equations that lead to the integral formulation of Schapery-type constitutive theories and Finite Difference (FD) schemes. This strategy is quite different from all the other strategies found in the literature. The second strategy is an improvement of recursive strategies, used by many authors, based on the integral formulation of the constitutive theory. The performances of the new algorithms are compared with those of existing strategies for various load histories and nonlinearities. It is shown that the newly developed strategy based on FD schemes can exhibit quadratic convergence rate when one time step is stored and 4th order convergence rate when two time steps are stored, which is a major improvement over the recursive strategies.     

Managing supply disruption through procurement strategy and price competition

When facing supply disruptions, the emergency procurement strategy and the optimal allocation procurement strategy are widely used strategies to manage supply risks. In this paper, buyers use these types of procurement strategies under the threat of supply disruption and engage in price competition. The structural properties of the procurement strategies are characterised by their reliability thresholds. We find that reliability thresholds play a critical role in buyer procurement strategy choices, which are related to the sales price, underage cost and differentials in unit procurement cost. A solution procedure is proposed to determine the equilibrium strategy profile. The effects of reliability levels and costs on the equilibrium prices, expected profits and equilibrium strategy profiles are explored. We extend the basic model to investigate the case of symmetric competition where buyers can freely choose their procurement strategy. The results show that in most cases, the competing buyers will choose the same strategy, whether an optimal allocation strategy with single sourcing or an emergency procurement strategy with dual sourcing. In a special parameter setting, the buyers will choose either strategy because they yield identical expected profits; this leads to multiple equilibria. We also find the equilibrium to be Pareto efficient.     

Coupled finite element – hierarchical boundary element methods for dynamic soil–structure interaction in the frequency domain

This paper discusses the coupling of finite element and fast boundary element methods for the solution of dynamic soil–structure interaction problems in the frequency domain. The application of hierarchical matrices in the boundary element formulation allows considering much larger problems compared to classical methods. Three coupling methodologies are presented and their computational performance is assessed through numerical examples. It is demonstrated that the use of hierarchical matrices renders a direct coupling approach the least efficient, as it requires the assembly of a dynamic soil stiffness matrix. Iterative solution procedures are presented as well, and it is shown that the application of such schemes to dynamic soil–structure interaction problems in the frequency domain is not trivial, as convergence can hardly be achieved if no relaxation procedure is incorporated. Aitken's Δ²‐method is therefore employed in sequential iterative schemes for the calculation of an optimized interface relaxation parameter, while a novel relaxation technique is proposed for parallel iterative algorithms. It is demonstrated that the efficiency of these algorithms strongly depends on the boundary conditions applied to each subdomain; the fastest convergence is observed if Neumann boundary conditions are imposed on the stiffest subdomain. The use of a dedicated solver for each subdomain hence results in a reduced computational effort. A monolithic coupling strategy, often used for the solution of fluid–structure interaction problems, is also introduced. The governing equations are simultaneously solved in this approach, while the assembly of a dynamic soil stiffness matrix is avoided. Copyright © 2013 John Wiley & Sons, Ltd.     

Optimal pricing for cloud service providers in a competitive setting

Cloud services are transforming business and government at an ever-increasing rate. As a form of cloud service, software as a service (SaaS) is one of the fast growing segments of the information technology and has become an attractive alternative to the on-premises software. In this paper, we study the optimal pricing strategies of a cloud service provider in an incumbent-entrant setting under user upgrade cost and switching cost. Our results show that in equilibrium the market structure is not unique. The specific market segmentation depends on the incumbent’s pricing strategy whether to provide discounted price to its old customers and the levels of user upgrade cost and switching cost. When faced with customers who are heterogeneous in the sensitivity to the related costs, the incumbent firm may need to offer a discount to the new customers rather than to those who have purchased from it. This implies that the entry of a SaaS firm into the market is a potential threat to the incumbent on-premises software firm, especially in capturing new customers from the untapped market.     

物流服务供应链两级合作的质量监控与协调

考虑一个物流服务集成商和提供商的两级供应链结构,建立了物流服务供应链两级合作的质量协调基本博弈模型,其中物流服务集成商可以选择质量监控和不监控,提供商可以按质量合同完成合作也可以选择欺骗,论文给出了该博弈模型的混合策略纳什均衡解.然后研究了物流服务集成商本身也存在受到惩罚可能时的多级质量协调的情况,模型进一步考虑了提供商之间的竞争情况对质量协调的影响,得出了新的纳什均衡解.上述模型分析结果表明,通过加强物流合作过程的监督与控制,减少信息不对称性,减少物流合作外包的层数,建立物流服务提供商的竞争机制,及时做好合作的回顾和评价工作等措施可以加强物流服务供应链两级合作的质量协调.     

An ascending price procurement auction for multiple items with unit supply

In this paper, a supply chain scenario is considered in which an original equipment manufacturer wishes to procure a set of items from a set of suppliers with private costs. Each supplier can provide at most one item. Two ascending price auctions are proposed to implement an efficient allocation for this model. The first converges to a unique competitive equilibrium price of the economy if suppliers bid truthfully. However, because no equilibrium strategy exists for the suppliers, a second auction is designed based on the first, which converges to a second unique competitive equilibrium price. Truthful bidding is a Bayesian Nash equilibrium strategy for suppliers in this auction. We show several practical advantages of our ascending auctions over traditional reverse auctions. Ascending auctions perform better than reverse auctions in two main aspects: (i) information revelation; and (ii) bidder cost determination. Simulation results are reported to validate these claims.     

Coordinated replenishment systems with discount opportunities

In many practical situations, coordination of replenishment orders for a family of items can lead to considerable cost savings. A well-known class of strategies for the case where cost savings are due to reduced joint ordering costs is the class of can-order strategies. However, these strategies, which are simple to implement in practice, do not take discount possibilities into account. We propose a method to incorporate discounts in the framework of can-order strategies. A continuous review multi-item inventory system is considered with independent compound Poisson demand processes for each of the individual items. Discounts are offered by the supplier as a percentage of the total dollar value whenever this value exceeds a given threshold. Starting from the can-order strategy as a basic decision rule, we develop a simple heuristic to evaluate these discount opportunities. The performance of the can-order strategy with discount evaluation is compared with that of another class of discount evaluation rules as proposed by Miltenburg and Silver.