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A Near-Optimal Exploration-Exploitation Approach for Assortment Selection

Shipra Agrawal, Vashist Avadhanula, Vineet Goyal, Assaf Zeevi
2016 Proceedings of the 2016 ACM Conference on Economics and Computation - EC '16  
We consider an online assortment optimization problem, where in every round, the retailer offers a Kcardinality subset (assortment) of N substitutable products to a consumer, and observes the response.  ...  We also establish a lower bound, by showing that any algorithm must incur a regret of Ω( N T /K) for K < N . This establishes that the performance of our algorithm is tight for constant K.  ...  exploration (learning consumer preferences) and exploitation (selecting the optimal assortment), and this variant of the problem is the subject of the present paper.  ... 
doi:10.1145/2940716.2940779 dblp:conf/sigecom/AgrawalAGZ16 fatcat:4jxtq3tgnffgvkglq3dvrpzrk4

Optimal Dynamic Assortment Planning with Demand Learning

Denis Sauré, Assaf Zeevi
2013 Manufacturing & Service Operations Management  
We develop a family of dynamic policies that judiciously balance the aforementioned tradeoff between exploration and exploitation, and prove that their performance cannot be improved upon in a precise  ...  Given limited display capacity and no a priori information on consumers' utility, the retailer must select which subset of products to offer.  ...  Indeed, this is the approach in Caro and Gallien (2007) who use a dynamic programming formulation and Bayesian learning approach to solve the exploration versus exploitation trade-off optimally (see  ... 
doi:10.1287/msom.2013.0429 fatcat:kbexan2dxzb6pibhg3ljvhkjsi

Modified Artificial Bee Colony (ABC) Algorithm using Dynamic Technique

Mirza Samiulla Beg, Akhilesh A. Waoo
2021 Asian Journal of Managerial Science  
The artificial Bee Colony Algorithm is a maximum optimization technique. It has been used in various research papers.  ...  These EAs are wont to acquire near-optimal solutions for NP-Hard discretional optimization issues.  ...  During a robust search process, exploration, and exploitation processes must be administered simultaneously (Kang et al., 2009) .  ... 
doi:10.51983/ajes-2021.10.1.2863 fatcat:6sp5xqjj2vfcronf3tp4uafm6q

MNL-Bandit: A Dynamic Learning Approach to Assortment Selection [article]

Shipra Agrawal, Vashist Avadhanula, Vineet Goyal, Assaf Zeevi
2018 arXiv   pre-print
Existing methods for this problem follow an "explore-then-exploit" approach, which estimate parameters to a desired accuracy and then, treating these estimates as if they are the correct parameter values  ...  We consider a dynamic assortment selection problem, where in every round the retailer offers a subset (assortment) of N substitutable products to a consumer, who selects one of these products according  ...  A. Zeevi is supported in part by NSF Grants NetSE-0964170 and BSF-2010466.  ... 
arXiv:1706.03880v2 fatcat:7re5aw3sjnenrmttlg5x4x43hu

Evolutionary Algorithms with Dissortative Mating on Static and Dynamic Environments [chapter]

Carlos M., Agostinho C.
2008 Advances in Evolutionary Algorithms  
In addition, diverse search stages usually call for different balance between exploration and exploitation mechanisms.  ...  The new approaches are compared with standard GA and CHC on some well-known test functions and on the problem of selecting the optimal set of weights in a multilayer perceptron.  ...  Aim of the book is to present recent improvements, innovative ideas and concepts in a part of a huge EA field.  ... 
doi:10.5772/6130 fatcat:727yh7p2ijgulpsiduk3f4x2ge

Assortative Mating Drastically Alters the Magnitude of Error Thresholds [chapter]

Gabriela Ochoa, Klaus Jaffe
2006 Lecture Notes in Computer Science  
Here, through a simulation model based on genetic algorithms, we incorporate assortative mating and explore its effect on the magnitude of error thresholds.  ...  destroyed more frequently than selection can reproduce them.  ...  between exploitation and exploration [17, 19] Methods We studied four fitness landscapes.  ... 
doi:10.1007/11844297_90 fatcat:pb3i6v75rbdk7dvmbimxycfi74

Evolutionary Processes in Complex Networks and Small Worlds

D S Vlachos, K J Parousis-Orthodoxou
2013 Journal of Physics, Conference Series  
Moreover, it has been founded that the hierarchical or modular nature of complex networks accelerates the convergent of a hybrid genetic algorithm applied in a rather complex search space.  ...  In this work, we examine the application of evolutionary processes on these systems in order to derive useful results for human dynamics modeling.  ...  An early result from research on genetic algorithms was the mathematical characterization of adaptation as a near-optimal trade off between exploitation of traits that have been already been found to be  ... 
doi:10.1088/1742-6596/410/1/012081 fatcat:gvwd4marirhptpqtxqwgqbpucq

Learning to Optimize via Information-Directed Sampling

Daniel Russo, Benjamin Van Roy
2018 Operations Research  
We propose information-directed sampling -a new algorithm for online optimization problems in which a decision-maker must balance between exploration and exploitation while learning from partial feedback  ...  We establish an expected regret bound for information-directed sampling that applies across a very general class of models and scales with the entropy of the optimal action distribution.  ...  Conclusion This paper has proposed information-directed sampling -a new algorithm for balancing between exploration and exploitation.  ... 
doi:10.1287/opre.2017.1663 fatcat:rnzygiakdrgnnmhnlhumggkd7i

Memetic Search in Differential Evolution Algorithm

Sandeep Kumar, Vivek Kumar Sharma, Rajani Kumari
2014 International Journal of Computer Applications  
DE is a well known and uncomplicated population based probabilistic approach for comprehensive optimization.  ...  Differential Evolution (DE) is a renowned optimization stratagem that can easily solve nonlinear and comprehensive problems.  ...  INTRODUCTION Population-based optimization algorithms find near-optimal solutions to the easier said than done optimization problems by inspiration from nature or natural entities.  ... 
doi:10.5120/15582-4406 fatcat:oiafxupetjchnjinzlifabyzq4

MNL-Bandits under Inventory and Limited Switches Constraints [article]

Hongbin Zhang, Yu Yang, Feng Wu, Qixin Zhang
2022 arXiv   pre-print
Such a setting suits the case when an online retailer wants to dynamically optimize the assortment selection for a population of customers.  ...  Optimizing the assortment of products to display to customers is a key to increasing revenue for both offline and online retailers.  ...  Therefore, it is nature to cast assortment selection as an online learning problem where the key is to trade off between exploration and exploitation.  ... 
arXiv:2204.10787v1 fatcat:4yrrsgijf5ddhhp2fjsygoa6ea

Dynamic Assortment with Demand Learning for Seasonal Consumer Goods

Felipe Caro, Jérémie Gallien
2007 Management science  
It yields a closed-form dynamic index policy capturing the key exploration versus exploitation trade-off and associated suboptimality bounds.  ...  How should such retail firms modify their product assortment over time in order to maximize overall profits for a given selling season?  ...  Finally, the second author is indebted to Martha Nieto for a conversation about Zara that sparked his interest in fast-fashion companies and was key to the genesis of this project.  ... 
doi:10.1287/mnsc.1060.0613 fatcat:s2zxaxjm6zgmzhhind4snnyyci

Solving Cargo Loading Problem Using Simulated Annealing Technique

Azme Khamis, Kek Sei Long, Low Siau Yin
2020 The International Journal of Science & Technoledge  
It is a method that provides good quality solution which approaches to the exact solution of the optimization problem.  ...  The average of near optimal solution is around 120,000 cm 2 therefore it provides a high-quality near optimal solution by comparing with the near optimal solution obtained by other parameters.  ...  The last objective is the near optimal solution of 126,948 cm 2 for the area that covered by cargoes in the container.  ... 
doi:10.24940/theijst/2020/v8/i7/st2007-017 fatcat:yu35bpdi3behbo7ehg5twdrqve

Learning to Optimize via Information-Directed Sampling [article]

Daniel Russo, Benjamin Van Roy
2017 arXiv   pre-print
We propose information-directed sampling -- a new approach to online optimization problems in which a decision-maker must balance between exploration and exploitation while learning from partial feedback  ...  We establish an expected regret bound for information-directed sampling that applies across a very general class of models and scales with the entropy of the optimal action distribution.  ...  This work was generously supported by a research grant from Boeing, a Marketing Research Award from Adobe, and the Burt and Deedee McMurty Stanford Graduate Fellowship.  ... 
arXiv:1403.5556v7 fatcat:vuyvczp6afg5jar6unibbtwlhm

Assessment of the assortment potential of the growing stock – a photogrammetry based approach for an automatized grading of sample trees

Christine Fürst, Gérard Nepveu
2006 Annals of Forest Science  
A total of eight Norway spruces (Picea abies, Karst.) and eight Scots pines (Pinus sylvestris L.) was selected as sample material for the development of the classification process in eCognition.  ...  In the context of forest inventory, the presented approach can support the acquirement of detailed sample-tree-based information on the assortment distribution at the level of management planning units  ...  Figure 1 . 1 Percentage deviation (absolute value) measured: estimated diameter per meter height for 6 selected sample trees (near distance photos).  ... 
doi:10.1051/forest:2006078 fatcat:chz76py2djf3zc75furmbnza2q

On community detection in real-world networks and the importance of degree assortativity

Marek Ciglan, Michal Laclavík, Kjetil Nørvåg
2013 Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '13  
We then examine the possibility of exploiting the latter by weighting edges of a network with the aim to improve the community detection outputs for networks with assortative community structure.  ...  Motivated by the observation that there is a class of networks for which the community detection methods fail to deliver good community structure, we examine the assortativity coefficient of ground-truth  ...  Acknowledgements We would like to thank the anonymous reviewers for their very helpful comments that have significantly improved this paper.  ... 
doi:10.1145/2487575.2487666 dblp:conf/kdd/CiglanLN13 fatcat:uxmqjsaeljf4noeq3koq5w63m4
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