Pareto analysis of supply chain contracts under satisficing objectives

Supply chain coordination has become critical to firms as increased pressure is placed on them to improve performance. We evaluate the performance of Push, Pull, and Advance-purchase discount (APD) contracts in a manufacturer-retailer supply chain where one or both firms have a satisficing objective of maximizing the probability of achieving a target profit. We identify the resulting operational modes of the supply chain and potential conflicts over the preferred contracts under the Push, Pull, and APD contracts. When both firms are satisficing, conflict over the preferred contract arises when the manufacturer has an ambitious profit target or the retailer has a low profit target. We show that the Push contract can result in a large decrease in the expected profit of a risk-neutral manufacturer when the retailer maximizes the probability of achieving her maximum expected profit. We find that a modified buy-back and profit guarantee contracts can provide significant Pareto improvement over Push or APD contracts when the manufacturer is risk-neutral and the retailer is satisficing, while revenue-sharing contracts cannot. In contrast, revenue sharing and modified buy-back contracts are Pareto dominant under certain conditions when the manufacturer is satisficing and the retailer is risk-neutral.     

Algorithms for Pareto optimal exchange with bounded exchange cycles

We consider exchange markets with single-unit endowments and demands where there is a bound on the size of the exchange cycles. The computational problem we study is that of computing a Pareto optimal and individually rational allocation. We present polynomial-time algorithms to compute a Pareto optimal and individually rational allocation when preferences are strict, the exchange bound is two, or when Pareto optimality is replaced with weak Pareto optimality.     

Existence of a pareto equilibrium

In this paper, we investigate the existence of Pareto equilibria in multicriteria games. The investigation is carried out in two ways: one follows the fixed-point technique, and the other utilizes other tools. Several sufficient conditions are presented to guarantee the existence of a Pareto equilibrium.This research was supported by NSFC under Grant No. G-78-900011 and by BMADIS. The author is grateful to the referees for supplying several valuable comments and suggestions.     

利用数学模型进行资源量评价与勘探开发经济分析

本文综合叙述了对石油或天然气资源量的估计及验证方法，并且提出了在经济效益最佳的前提下，如何求出令后几年的年发现率Ｒ１（Ｉ）。     

Emergence of power-law in a market with mixed models

We investigate the problem of wealth distribution from the viewpoint of asset exchange. Robust nature of Pareto's law across economies, ideologies and nations suggests that this could be an outcome of trading strategies. However, the simple asset exchange models fail to reproduce this feature. A Yardsale (YS) model in which amount put on the bet is a fraction of minimum of the two players leads to condensation of wealth in hands of some agent while theft and fraud (TF) model in which the amount to be exchanged is a fraction of loser's wealth leads to an exponential distribution of wealth. We show that if we allow few agents to follow a different model than others, i.e., there are some agents following TF model while rest follow YS model, it leads to distribution with power-law tails. Similar effect is observed when one carries out transactions for a fraction of one's wealth using TF model and for the rest YS model is used. We also observe a power-law tail in wealth distribution if we allow the agents to follow either of the models with some probability.     

On the cardinality of the Pareto set in bicriteria shortest path problems

Computing shortest paths with two or more conflicting optimization criteria is a fundamental problem in transportation and logistics. We study the problem of finding all Pareto-optimal solutions for the multi-criteria single-source shortest-path problem with nonnegative edge lengths. The standard approaches are generalizations of label-setting (Dijkstra) and label-correcting algorithms, in which the distance labels are multi-dimensional and more than one distance label is maintained for each node. The crucial parameter for the run time and space consumption is the total number of Pareto optima. In general, this value can be exponentially large in the input size. However, in various practical applications one can observe that the input data has certain characteristics, which may lead to a much smaller number—small enough to make the problem efficiently tractable from a practical viewpoint. For typical characteristics which occur in various applications we study in this paper whether we can bound the size of the Pareto set to a polynomial size or not. These characteristics are also evaluated (1) on a concrete application scenario (computing the set of best train connections in view of travel time, fare, and number of train changes) and (2) on a simplified randomized model. It will turn out that the number of Pareto optima on each visited node is restricted by a small constant in our concrete application, and that the size of the Pareto set is much smaller than our worst case bounds in the randomized model. A preliminary short version of this paper appeared in the Proceedings of the 5th Workshop on Algorithm Engineering (WAE 2001), LNCS 2141, Springer Verlag, pp. 185–197 (2001) under the title “Pareto shortest paths is often feasible in practice.”     

Simulation of certain multivariate generalized Pareto distributions

The investigation of multivariate generalized Pareto distributions (GPDs) has begun only recently. For further progress with these distributions simulation methods are an important part. We describe several methods of simulating GPDs, beginning with an efficient method for the logistic GPD. The algorithm is based on the Shi transformation, which was already used for the simulation of multivariate extreme value distributions (EVDs) of logistic type. In the sequel another algorithm is presented simulating a broader class of GPDs. Due to its numerical complexity it is only practicably applicable in low dimensions. A method is given to generate unconditional GPD random vectors from conditionally GPD distributed random vectors. A short application of the simulation methods in the analysis of a real hydrological data set concludes the article. The simulation algorithms are available on the author’s home page .      

Chains of reinsurance: Non-cooperative equilibria and pareto optimality

The purpose of this paper is to extend Gerber's seminal paper on chains of reinsurance in three directions: (i) to throw some light on the rationale of finite chains under the Stackelberg equilibria introduced by Gerber, (ii) to propose new non-cooperative equilibrium concepts, of the Cournot type, which allow the first reinsured to transfer more than 50 percent of its risk if the risk aversion is the same for all companies, and (iii) to compare the Pareto optimal and the different equilibrium transfers of risk between reinsurers.     

Weak Pareto optimality of multiobjective problems in a locally convex linear topological space

Several corrections to Ref. 1 are pointed out.     

Lifetime distribution and estimation problems of consecutive-k-out-of-n:F systems

Explicit formula is given for the lifetime distribution of a consecutive-k-out-of-n:F system. It is given as a linear combination of distributions of order statistics of the lifetimes of n components. We assume that the lifetimes are independent and identically distributed. The results should make it possible to treat the parametric estimation problems based on the observations of the lifetimes of the system. In fact, we take up, as some examples, the cases where the lifetimes of the components follow the exponential, the Weibull, and the Pareto distributions, and obtain feasible estimators by moment method. In particular, it is shown that the moment estimator is quite good for the exponential case in the sense that the asymptotic efficiency is close to one.This research was partially supported by the ISM Cooperative Research Program (94-ISM-CRP-5).