Algorithmic fairness is typically studied from the perspective of predictions. Instead, here we investigate recourse actions suggested to individuals remedy an unfavourable classification. We propose two new fair-ness criteria at group and individual level, which—unlike prior work on equalising average group-wise distance decision boundary—explicitly account for causal relationships between fea...

We consider the bin packing problem in a fully-dynamic setting, where new items can arrive and old items may depart. The objective here is to obtain algorithms achieving low asymptotic competitive ratio while changing the packing sparingly between updates. We associate with each item i a movement cost ci ≥ 0. We wish to achieve good approximation guarantees while incurring a movement cost of β ...

This paper addresses the problem of maximizing the expected size of a matching in the case of unreliable vertices and/or edges. The assumption is that upon failure, remaining vertices that have not been matched may be subject to a new assignment. This process may be repeated a given number of times, and the objective is to end with the overall maximum number of matched vertices. The origin of t...

The simple integer recourse (SIR) function of a decision variable is the expectation of the integer roundup of the shortage/surplus between a random variable with a known distribution and the decision variable. It is the integer analogue of the simple (continuous) recourse function in two stage stochastic linear programming. Structural properties and approximations of SIR functions have been ex...

We propose an algorithm for multistage stochastic linear programs with recourse where random quantities in different stages are independent. The algorithm approximates successively expected recourse functions by building up valid cutting planes to support these functions from below. In each iteration, for the expected recourse function in each stage, one cutting plane is generated using the dua...

This paper is concerned with multi-period sequential decision problems for financial asset allocation. A model is proposed in which periodic optimal portfolio adjustments are determined with the objective of minimizing a cumulative risk measure over the investment horizon, while satisfying portfolio diversity constraints at each period and achieving or exceeding a desired terminal expected weal...

Sorting, a classical combinatorial process, forms the bedrock of numerous algorithms with varied applications. A related problem involves efficiently finding the corresponding ranks of all the elements – catering to rank queries, data partitioning and allocation, etc. Although, the element ranks can be subsequently obtained by initially sorting the elements, such procedures involve O(n logn) co...

Modern clouds and datacenters are rapidly growing in scale and complexity. They contain an eclectic set of hardware, networks, applications, and virtual machines that give rise to complex emergent behaviour, unobservable when components are tested individually. Problem diagnosis in these environments is especially difficult, as it can require developers to have expert knowledge about every deta...

Prime cost determinations can increase managerial effectiveness in budget allocation and strategic planning. This study was designed to calculate the prime cost of clinical laboratory services in Tehran Valiasr Hospital using the activity-based costing (ABC) model. The highest costs were for human recourses (44%) and the lowest for energy (5%). The largest proportion of activities (97%) was by ...