Co-movement analysis has a significant role in recourse allocation, risk management, etc. This study uses the novel approach of wavelet coherence in continuous wavelet transform framework to investigate the correlation dynamic and spillover effect of 10 main sector indices of Tehran Stock Exchange, in time and frequency domains. Analyzing the data indicates that correlation structure among TSE ...

A stochastic version of a concentrator location problem is dealt with in which traffic demand at each terminal location is uncertain. The concentrator location problem is defined as to determine the following: (i) the numbers and locations of concentators that are to be open, and (ii) the allocation of terminals to concentrator sites. The problem is formulated as a stochastic multi-stage intege...

The allocation of surgeries to operating rooms (ORs) is a challenging combinatorial optimization problem. There is also significant uncertainty in the duration of surgical procedures, which further complicates assignment decisions. In this article, we present stochastic optimization models for the assignment of surgeries to ORs on a given day of surgery. The objective includes a fixed cost of o...

Many collusive agreements involve the exchange of self-reported sales data between competitors, which use them to monitor compliance with a target market share allocation. Such communication may facilitate collusion even if it is unverifiable cheap talk and underlying information becomes publicly available delay. The allow firms implement incentive-compatible reallocation mechanisms after unexp...

We introduce the problem of selecting patient-donor pairs in a kidney exchange program to undergo crossmatch test, and we model this selection as two-stage stochastic integer programming problem. The optimal solutions new formulation yield larger expected number realized transplants than previous approaches based on internal recourse or subset recourse. settle computational complexity by showin...

Algorithmic recourse recommendations inform stakeholders of how to act revert unfavorable decisions. However, existing methods may recommend actions that lead acceptance (i.e., the model's decision) but do not improvement underlying real-world state). To such is fooling predictor. We introduce a novel method, Improvement-Focused Causal Recourse (ICR), which involves conceptual shift: Firstly, w...

We consider modification of the recourse data, consisting of the second-stage parameters and the underlying distribution, as an approximation technique for solving two-stage recourse problems. This approach is applied to several specific classes of mixed-integer recourse problems; in each case, the resulting recourse problem is much easier to solve.