Finding Fair and Efficient Allocations for Matroid Rank Valuations

In this article, we present new results on the fair and efficient allocation of indivisible goods to agents whose preferences correspond to matroid rank functions . This is a versatile valuation class with several desirable properties (such as monotonicity and submodularity), which naturally lends itself to a number of real-world domains. We use these properties to our advantage; first, we show that when agent valuations are matroid rank functions, a socially optimal (i.e., utilitarian social welfare-maximizing) allocation that achieves envy-freeness up to one item (EF1) exists and is computationally tractable. We also prove that the Nash welfare-maximizing and the leximin allocations both exhibit this fairness/efficiency combination by showing that they can be achieved by minimizing any symmetric strictly convex function over utilitarian optimal outcomes. To the best of our knowledge, this is the first valuation function class not subsumed by additive valuations for which it has been established that an allocation maximizing Nash welfare is EF1. Moreover, for a subclass of these valuation functions based on maximum (unweighted) bipartite matching, we show that a leximin allocation can be computed in polynomial time. Additionally, we explore possible extensions of our results to fairness criteria other than EF1 as well as to generalizations of the above valuation classes.

Application of reinforcement learning for the optimization of clinch joint characteristics

Due to increasing challenges in the area of lightweight design, the demand for time- and cost-effective joining technologies is steadily rising. For this, cold-forming processes provide a fast and environmentally friendly alternative to common joining methods, such as welding. However, to ensure a sufficient applicability in combination with a high reliability of the joint connection, not only the selection of a best-fitting process, but also the suitable dimensioning of the individual joint is crucial. Therefore, few studies already investigated the systematic analysis of clinched joints usually focusing on the optimization of particular tool geometries against shear and tensile loading. This mainly involved the application of a meta-model assisted genetic algorithm to define a solution space including Pareto optima with all efficient allocations. However, if the investigation of new process configurations (e. g. changing materials) is necessary, the earlier generated meta-models often reach their limits which can lead to a significantly loss of estimation quality. Thus, it is mainly required to repeat the time-consuming and resource-intensive data sampling process in combination with the following identification of best-fitting meta-modeling algorithms. As a solution to this problem, the combination of Deep and Reinforcement Learning provides high potentials for the determination of optimal solutions without taking labeled input data into consideration. Therefore, the training of an Agent aims not only to predict quality-relevant joint characteristics, but also at learning a policy of how to obtain them. As a result, the parameters of the deep neural networks are adapted to represent the effects of varying tool configurations on the target variables. This provides the definition of a novel approach to analyze and optimize clinch joint characteristics for certain use-case scenarios.

Efficient Allocations in Double Auction Markets

This paper proposes a simple descriptive model of discrete-time double auction markets for divisible assets. As in the classical models of exchange economies, we consider a finite set of agents described by their initial endowments and preferences. Instead of the classical Walrasian-type market models, however, we assume that all trades take place in a centralized double auction where the agents communicate through sealed limit orders for buying and selling. We find that, under nonstrategic bidding, double auction clears with zero trades precisely when the agents’ current holdings are on the Pareto frontier. More interestingly, the double auctions implement Adam Smith’s “invisible hand” in the sense that, when starting from disequilibrium, repeated double auctions lead to a sequence of allocations that converges to individually rational Pareto allocations.

Altruism and efficient allocations in three-generation households

In this paper we test the efficiency of family resource allocation in three-generation households. Understanding how the so-called “squeezed middle” generation allocates resources towards the children and grandparents in the household will be increasingly important as populations age, and more elderly people become dependent upon their relations for financial support. Despite a large literature on household resource allocation in two-generation households (parents and children), to the best of our knowledge ours is the first study that includes the third generation. We present a theoretical model and conduct a discrete choice experiment in the context of reductions in the lifetime risk of developing coronary artery disease to verify the efficient resource allocation hypothesis. The data is obtained from a large sample of the Polish population. The sample consists of the middle generation members of three-generation households and hence WTP represents household value from the perspective of the “squeezed middle” parent. The results imply that household resource allocation is efficient. This has implications for understanding the likely response to government financial support aimed at supporting elderly people and their families.

Modeling Multi-Site Computation Offloading in Unreliable Cloud Environments

Offloading heavy computations from a mobile device to cloud servers can reduce the power consumption of the mobile device and improve the response time of mobile applications. However, the gains of offloading can be significantly affected by failures of cloud servers and network links. In this thesis, we propose a fault-aware, multi-site computation offloading model capable of finding efficient allocations of tasks to resources. Our model reduces both response time and energy consumption by incorporating the effect of failures and recovery mechanisms for various offloading allocations. In addition, we create a fault-injection framework to evaluate an allocation under various failure rates and recovery mechanisms. The experiments carried out with our fault-injection framework demonstrate that our fault-aware model can determine an allocation—based on the type of failures, failure rates, and the employed recovery mechanisms—that improves both response time and lower energy consumption compared to model without failures.

Modeling Multi-Site Computation Offloading in Unreliable Cloud Environments

Offloading heavy computations from a mobile device to cloud servers can reduce the power consumption of the mobile device and improve the response time of mobile applications. However, the gains of offloading can be significantly affected by failures of cloud servers and network links. In this thesis, we propose a fault-aware, multi-site computation offloading model capable of finding efficient allocations of tasks to resources. Our model reduces both response time and energy consumption by incorporating the effect of failures and recovery mechanisms for various offloading allocations. In addition, we create a fault-injection framework to evaluate an allocation under various failure rates and recovery mechanisms. The experiments carried out with our fault-injection framework demonstrate that our fault-aware model can determine an allocation—based on the type of failures, failure rates, and the employed recovery mechanisms—that improves both response time and lower energy consumption compared to model without failures.

Land Regulations, Tenure, and Land Use of Sri Lanka

Present land use and tenure of a country is a result of the social norms and regulations. Land use manifests a country's priorities with implications on the economic development. Land tenure has implications on the investment decisions on land and hence efficient allocations of land. Sri Lanka, a country with a history of king's reign, colonial rule and then an elected government has its unique journey in the evolution of laws and regulations and institutions governing land and the resultant land use. This chapter chronicles the evolution of laws and regulations and institutions governing agricultural land and the resultant land use and tenure arrangements. At present, the governance of agricultural land is complex as it involves many regulations and many competing institutions.

A study on online platforms’ price discrimination behavior and the same-side network effects

Purpose The purpose of this paper is to whether competition between platforms can be effective, thus leading to efficient allocations. Design/methodology/approach Based on the classic linear Hoteling model, this paper builds a two-period competition model for two competing platforms using two variants, namely, a discrimination pricing model and a unified pricing model. Findings In the case of the discrimination pricing model, the competition is moderate, and the two platforms split the market evenly in the first stage, while both platforms tended to offer preferential treatment to new users and set higher prices for regular customers in the second stage. Compared to the unified pricing model, in the first stage, the platform can provide a higher price that depends on the cross-network effect when it implements discrimination, and thus, obtains higher profits. However, in the second stage, fierce competition leads to the release of benefits, new and regular customers obtain lower prices and the platforms lose higher profits. In the long-run, discriminatory pricing is not the best option due to lower total profits. The two platforms will implement cooperative pricing or one platform becomes dominant. Originality/value Instead of focusing on the cross-network effects, this paper emphasizes the role of the same-side network effect on price discrimination regarding the platforms’ competition. The same-side network effects are investigated in relation to a discrimination pricing strategy and compared to a unified pricing strategy. Another innovative aspect is the study of these network effects in a dynamic setting based on a two-period competition model for two platforms.