Operations Research Letters最新文献

In the online hypergraph matching problem, hyperedges of size k over a common ground set arrive online in adversarial order. The goal is to obtain a maximum matching (disjoint set of hyperedges). A naïve greedy algorithm for this problem achieves a competitive ratio of $\frac{1}{k}$. We show that no (randomized) online algorithm has competitive ratio better than $\frac{2+o\left(1\right)}{k}$. If edges are allowed to be assigned fractionally, we give a deterministic online algorithm with competitive ratio $\frac{1-o\left(1\right)}{\ln \left(k\right)}$ and show that no online algorithm can have competitive ratio strictly better than $\frac{1+o\left(1\right)}{\ln \left(k\right)}$. Lastly, we give a $\frac{1-o\left(1\right)}{\ln \left(k\right)}$ competitive algorithm for the fractional edge-weighted version of the problem under a free disposal assumption.

Uncertainty reduction has recently been introduced in the robust optimization literature as a relevant special case of decision-dependent uncertainty. Herein, we identify two relevant situations in which the problem is polynomially solvable. We further provide insights into possible MILP reformulations and the strength of their continuous relaxations.

Clustering is an unsupervised learning technique for organizing complex datasets into coherent groups. A novel clustering algorithm is presented, with a simple grouping concept depending on only one hyperparameter, which makes it suitable for further extensions to any topology and space. It is compared to state-of-the-art algorithms, overall achieving a better performance independently on the structure and complexity of the data, making the proposed algorithm a valuable tool for real applications such as market segmentation, sentiment analysis and anomaly detection.

This paper derives a theoretical relation between the left and right slopes of the implied volatility curve with negative and positive price jumps. Empirical analysis using bitcoin options tick-by-tick data from Deribit exchange supported the theoretical findings that negative and positive jumps have reversal impacts on bitcoin options' implied volatility slopes even after the control of net-buying-pressure and realized positive and negative skewness measures.

Morris (1994) and Feinberg (2000) showed that a finite type space admits a common prior if and only if there is no agreeable bet in it.

We also consider finite type spaces and observe that the problem of computing a common prior is equivalent to considering the intersection of affine spaces spanned by the types of a player. Therefore, we can apply the Fredholm alternative and conclude that the computational complexity of computing a common prior is strongly polynomial.

Circulant TSP is an intriguing special case of the Traveling Salesman Problem, whose complexity remains an often-cited open problem. In this note, we present three results: We show that circulant TSP can be efficiently solved whenever the input number of vertices is a prime-squared; we show that the $\{1,2\}$-TSP can be easily and efficiently solved when specialized to circulant instances; and we present a substantially-improved approximation factor for finding a minimum-cost Eulerian connected sub-(multi)graph on two-stripe circulant instances.

This paper considers one-warehouse multiple-retailer inventory systems. The retailers are non-identical and face Poisson demand processes. We consider an integer-ratio policy in which each retailer orders in a fixed interval that is either an integer or integer-ratio multiple of the warehouse's reorder interval. Base-stock policy and virtual allocation are assumed. We show that cost evaluations at the retailers are completely separable, leading to a simple approach to develop an optimal integer-ratio policy for a two-level distribution system with heterogeneous retailers.

Given k blue cities, k red cities and a $2k\times 2k$ distance matrix, the task in the bipartite travelling salesman problem is to find a shortest tour which alternately visits blue and red cities. We consider the special case of Van der Veen distance matrices and show that it remains NP-hard in general but can be solved in $O\left(k^2\right)$ time when all vertices with odd indices are blue and all with even indices are red.

In this paper, we propose a dynamical model to capture cascading failures among interconnected organizations in the global financial system and develop a framework to investigate under which conditions organizations remain healthy. The contribution of this paper is threefold: i) we develop a dynamical model that describes the time evolution of the organizations' equity values given nonequilibrium initial conditions; ii) we characterize the equilibria for this model; and iii) we provide a computational method to anticipate potential propagation of failures.

We study how risk aversion affects equilibrium bidding strategies in a first-price security-bid auction. We show that if the bidder's expected utility is concave and their marginal expected utility decreases as the degree of risk aversion increases – conditions that are shown to be satisfied under some conditions for four prominent securities (cash, equity, debt, and call option) –, the increase in the degree of risk aversion leads to lower bids in equilibrium.