84 citations · 126 across the 21 of their papers we have counts for
24 papers
Assortment Optimization under the Mallows Model: Independent-Utility Choice Equivalence and Its Algorithmic Implications
Danny Segev
The Mallows model is a well-established construct in preference modeling, describing random rankings through their Kendall-Tau distance from a reference permutation. Its compact pa…
Resource-Constrained Joint Replenishment via Power-of- Policies
Danny Segev
The continuous-time joint replenishment problem has long served as a foundational inventory management model. Even though its unconstrained setting has seen recent algorithmic adva…
Economic Warehouse Lot Scheduling: Breaking the 2-Approximation Barrier
Danny Segev
The economic warehouse lot scheduling problem is a foundational inventory-theory model, capturing computational challenges in dynamically coordinating replenishment decisions for m…
Economic Warehouse Lot Scheduling: Approximation Schemes via Efficiently-Representable DP-Encoded Policies
Danny Segev
In this focused technical paper, we present long-awaited algorithmic advances toward the efficient construction of near-optimal replenishment policies for a true inventory manageme…
Approximation Schemes for Sequential Hiring Problems
Danny Segev, Uri Stein
The main contribution of this paper resides in providing novel algorithmic advances and analytical insights for the sequential hiring problem, a recently introduced dynamic optimiz…
Approximation Algorithms for Fair Repetitive Scheduling
Danny Hermelin, Danny Segev, Dvir Shabtay
We consider a recently introduced fair repetitive scheduling problem involving a set of clients, each asking for their associated job to be daily scheduled on a single machine acro…
Improved Approximation Guarantees and Hardness Results for MNL-Driven Product Ranking
Danny Segev, Gidi Steinberg
In this paper, we address open computational questions regarding the market share ranking problem, recently introduced by Derakhshan et al. (2022). Their modelling framework incorp…
Near-Optimal Dynamic Policies for Joint Replenishment in Continuous/Discrete Time
Danny Segev
While dynamic policies have historically formed the foundation of most influential papers dedicated to the joint replenishment problem, we are still facing profound gaps in our str…
New Approximation Guarantees for The Inventory Staggering Problem
Noga Alon, Danny Segev
Since its inception in the mid-60s, the inventory staggering problem has been explored and exploited in a wide range of application domains, such as production planning, stock cont…
New Approximation Guarantees for The Economic Warehouse Lot Scheduling Problem
Danny Segev
In this paper, we present long-awaited algorithmic advances toward the efficient construction of near-optimal replenishment policies for a true inventory management classic, the ec…
Revenue Maximization in Choice-Based Matching Markets
Dan Nissim, Danny Segev, Alfredo Torrico
The primary contribution of this paper resides in devising constant-factor approximation guarantees for revenue maximization in two-sided matching markets with general pairwise rew…
Improved Approximation Guarantees for Joint Replenishment in Continuous Time
Danny Segev
The primary objective of this work is to revisit and revitalize one of the most fundamental models in deterministic inventory management, the continuous-time joint replenishment pr…
Maximum Load Assortment Optimization: Approximation Algorithms and Adaptivity Gaps
Omar El Housni, Marouane Ibn Brahim, Danny Segev
Motivated by modern-day applications such as Attended Home Delivery and Preference-based Group Scheduling, where decision makers wish to steer a large number of customers toward ch…
The Continuous-Time Joint Replenishment Problem: -Optimal Policies via Pairwise Alignment
Danny Segev
The main contribution of this paper resides in developing a new algorithmic approach for addressing the continuous-time joint replenishment problem, termed -pairwise alignment.…
A Constructive Prophet Inequality Approach to The Adaptive ProbeMax Problem
Guillermo Gallego, Danny Segev
In the adaptive ProbeMax problem, given a collection of mutually-independent random variables , our goal is to design an adaptive probing policy for sequentially…
Near-Optimal Adaptive Policies for Serving Stochastically Departing Customers
Danny Segev
We consider a multi-stage stochastic optimization problem originally introduced by Cygan et al. (2013), studying how a single server should prioritize stochastically departing cust…
An Approximate Dynamic Programming Approach to The Incremental Knapsack Problem
Ali Aouad, Danny Segev
We study the incremental knapsack problem, where one wishes to sequentially pack items into a knapsack whose capacity expands over a finite planning horizon, with the objective of…
Approximation Algorithms for The Generalized Incremental Knapsack Problem
Yuri Faenza, Danny Segev, Lingyi Zhang
We introduce and study a discrete multi-period extension of the classical knapsack problem, dubbed generalized incremental knapsack. In this setting, we are given a set of item…
Efficient Approximation Schemes for Stochastic Probing and Selection-Stopping Problems
Danny Segev, Sahil Singla
In this paper, we propose a general framework to design {efficient} polynomial time approximation schemes (EPTAS) for fundamental stochastic combinatorial optimization problems. Gi…
A Polynomial-Time Approximation Scheme for The Airplane Refueling Problem
Iftah Gamzu, Danny Segev
We study the airplane refueling problem which was introduced by the physicists Gamow and Stern in their classical book Puzzle-Math (1958). Sticking to the original story behind thi…
Improved Bounds for Online Preemptive Matching
Leah Epstein, Asaf Levin, Danny Segev +1
When designing a preemptive online algorithm for the maximum matching problem, we wish to maintain a valid matching M while edges of the underlying graph are presented one after th…
A Sublogarithmic Approximation for Highway and Tollbooth Pricing
Iftah Gamzu, Danny Segev
An instance of the tollbooth problem consists of an undirected network and a collection of single-minded customers, each of which is interested in purchasing a fixed path subject t…
Improved approximation guarantees for weighted matching in the semi-streaming model
Leah Epstein, Asaf Levin, Julian Mestre +1
We study the maximum weight matching problem in the semi-streaming model, and improve on the currently best one-pass algorithm due to Zelke (Proc. of STACS2008, pages 669-680) by d…
Scheduling with Outliers
Anupam Gupta, Ravishankar Krishnaswamy, Amit Kumar +1
In classical scheduling problems, we are given jobs and machines, and have to schedule all the jobs to minimize some objective function. What if each job has a specified profit, an…