The Unreasonable Fairness of Maximum Nash Welfare
The maximum Nash welfare (MNW) solution—which selects an allocation that maximizes the product of utilities—is known to provide outstanding fairness guarantees when allocating divisible goods. And while it seems to lose its luster when applied to indivisible goods, we show that, in fact, the MNW solution is strikingly fair even in that setting. In particular, we prove that it selects allocations that are envy-free up to one good—a compelling notion that is quite elusive when coupled with economic efficiency. We also establish that the MNW solution provides a good approximation to another popular (yet possibly infeasible) fairness property, the maximin share guarantee, in theory and—even more so—in practice. While finding the MNW solution is computationally hard, we develop a nontrivial implementation and demonstrate that it scales well on real data. These results establish MNW as a compelling solution for allocating indivisible goods and underlie its deployment on a popular fair-division website.
The maximum Nash welfare (MNW) solution — which selects an allocation that maximizes the product of utilities — is known to provide outstanding fairness guarantees when allocating divisible goods. And while it seems to lose its luster when applied to indivisible goods, we show that, in fact, the MNW solution is unexpectedly, strikingly fair even in that setting. In particular, we prove that it selects allocations that are envy free up to one good — a compelling notion that is quite elusive when coupled with economic efficiency. We also establish that the MNW solution provides a good approximation to another popular (yet possibly infeasible) fairness property, the maximin share guarantee, in theory and — even more so — in practice. While finding the MNW solution is computationally hard, we develop a nontrivial implementation, and demonstrate that it scales well on real data. These results lead us to believe that MNW is the ultimate solution for allocating indivisible goods, and underlie its deployment on a popular fair division website.
Russian society has a dual structure. On the one hand, the state has created formal professional castes, to which it allocates resources based on the principle of welfare-state distributive justice. On the other hand, there exist informal “corporations”. Politics in Russia revolves around the conflict between these two principles of order. On one side are those who want to allocate resources according to the principles of a deeply socialist caste society; on the other side are the members of different regions, sectors, concerns, clans, or ethnic groups who want to see resources allocated according to the unwritten “rules” of a fluctuating hierarchy of these “corporations”.
This book constitutes the proceedings of the 35th International Conference on Application and Theory of Petri Nets and Concurrency, PETRI NETS 2014, held in Tunis, Tunisia, in June 2014. The 15 regular papers and 4 tool papers presented in this volume were carefully reviewed and selected from 48 submissions. In addition the book contains 3 invited talks in full paper length. The papers cover various topics in the field of Petri nets and related models of concurrency.
There is the description of the conception "resource allocation". Increase in speed as a result of parallelization of work is demonstrated. As an example, the investigation of task from the contest "TRIZformashka 2015" is given.
The article addresses the problem of multi-project resource allocation under uncertainty. It discusses the main approaches to resource allocation across the projects in an innovative investment portfolio and describes the basic models for multi-project resource allocation. The authors present a model of effective resource allocation under uncertainty that takes into account the dependence of job duration on the completeness of allocated resources. Examples of simulation-based practical solutions to resource allocation problem are also given.
A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traﬃc is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the ﬁnal node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties. This model is described by a ﬁnite-dimensional system of diﬀerential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of diﬀerential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.