E
Erik Rolland
Researcher at University of California, Merced
Publications - 61
Citations - 2053
Erik Rolland is an academic researcher from University of California, Merced. The author has contributed to research in topics: Tabu search & Heuristic (computer science). The author has an hindex of 22, co-authored 58 publications receiving 1857 citations. Previous affiliations of Erik Rolland include University of California & University of California, Berkeley.
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The design of reverse distribution networks: Models and solution procedures
TL;DR: This paper discusses reverse distribution, and proposes a mathematical programming model for a version of this problem that complements a heuristic concentration procedure, where sub-problems with reduced sets of decision variables are iteratively solved to optimality.
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An efficient tabu search procedure for the p-Median Problem
TL;DR: In this article, a new solution heuristic for the p-Median problem is presented, based on tabu search principles, and uses short term and long term memory, as well as strategic oscillation and random tabu list sizes.
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Decision support for disaster management
TL;DR: This paper proposes a decision-support system for disaster response and recovery using hybrid meta-heuristics, which aims to address the challenges of timely and appropriate task assignment and sequencing in the face of operational constraints.
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Knowledge-sharing in virtual communities: familiarity, anonymity and self-determination theory
Cheolho Yoon,Erik Rolland +1 more
TL;DR: The results show that perceived competence and perceived relatedness influence knowledge-sharing behaviours in virtual communities; however, perceived autonomy does not influence knowledge -sharing behaviours; familiarity influences positively perceived competence, and anonymity influences negatively perceived autonomy and perceivedrelatedness.
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Tabu search for graph partitioning
TL;DR: It is demonstrated that tabu search is superior to other solution approaches for the uniform graph partitioning problem both with respect to solution quality and computational requirements.