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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Posts
Future Blog Post
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Blog Post number 4
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Blog Post number 3
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Blog Post number 2
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Blog Post number 1
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portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
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publications
Fix-and-Optimize Heuristic and MP-based Approaches for Capacitated Lot Sizing Problem with Setup Carryover, Setup Splitting and Backlogging.
Published in 2015 The 6th International Workshop on Lot Sizing, Montréal, Canada, 2015
Abstract: In this paper, we focus on the single-level, multi-item capacitated lot sizing problem with setup carryover, setup splitting and backlogging. Although the capacitated lot sizing has been investigated with many different features from researchers, the simultaneous consideration of setup carryover and setup splitting is relatively new. This consideration is beneficial to reduce costs and produce feasible production schedule. In this research, we use a simple plant location reformulation of the original mixed integer programming model to obtain a tighter relaxation. We also add valid inequalities to further tighten the formulation. A fix-and-optimize heuristic with two-step product decomposition and period decomposition strategy is proposed to solve the formulation. The computational results show the effectiveness of the approach, achieving 6% and 8% average optimality gap of data with and without backlogging, respectively.
Failure Mitigation and Restoration in Interdependent Networks via Mixed-integer Optimization.
Published in IEEE Transactions on Network Science and Engineering, 2020
Abstract: We propose a new optimization model for determining optimal mitigation and restoration strategies for coupled interdependent networks in the context of preserving and/or restoring the maximum flow through the entire networked system, subject to cascading node failures that may be caused by disruptions of a subset of “seed nodes” at an initial time step. Previous related studies mainly focused on “static” strategies to mitigate cascading failures. However, our model allows one to identify “dynamic” strategies for step-by-step failure propagation, given initial seed node disruptions. Moreover, the proposed model accounts for backup arc capacity and node fortification to mitigate the impact of further failure cascades on network performance. The objective is to restore network performance during a finite recovery planning horizon at total minimal cost. We formulate this problem by mixed-integer optimization, and derive valid inequalities using the substructure of the problem. We report a summary of computational experiments to demonstrate the strength and effectiveness of the inequalities when compared to solving the problem with a commercial optimization solver.
A Cutting Plane Method for Least Cost Influence Maximization.
Published in Computational Data and Social Networks - 9th International Conference, CSoNet 2020, Dallas, TX, 2021
Abstract: We study the least cost influence maximization problem, which has potential applications in social network analysis, as well as in other types of networks. The focus of this paper is on mixed-integer programming (MIP) techniques for the considered problem. The standard arc-based MIP formulation contains a substructure that is a relaxation of the mixed 0-1 knapsack polyhedron. We give a new exponential class of facet-defining inequalities from this substructure and an exact polynomial time separation algorithm for the inequalities. We report preliminary computational results to illustrate the effect of these inequalities.
A Polyhedral Approach to Least Cost Influence Maximization in Social Networks.
Published in Journal of Combinatorial Optimization, 2023
Abstract: The least cost influence maximization problem aims to determine minimum cost of partial (e.g., monetary) incentives initially given to the influential spreaders on a social network, so that these early adopters exert influence toward their neighbors and prompt influence propagation to reach a desired penetration rate by the end of cascading processes. We first conduct polyhedral analysis on a substructure that describes influence propagation assuming influence weights are unequal, linear and additively separable. Two classes of facet-defining inequalities based on a mixed 0–1 knapsack set contained in this substructure are proposed. We characterize another exponential class of valid and facet-defining inequalities utilizing the concept of minimum influencing subset. We show that these inequalities can be separated in polynomial time efficiently. Furthermore, a polynomial-time dynamic programming recursion is presented to solve this problem on a simple cycle graph. For arbitrary graphs, we propose a new exponential class of valid inequalities that dominates the cycle elimination constraints and an efficient separation algorithm for them. A compact convex hull description for a special case is presented. We illustrate the effectiveness of these inequalities via a delayed cut generation algorithm in the computational experiments.
talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.