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Heuristics for the 0–1 min-knapsack problem

TLDR
This work studies a greedy-type heuristic and refined it to obtain a new heuristic with a worst-case bound of 3/2 that is applicable to the 0-1 min-knapsack problem.
Abstract
textThe 0-1 min-knapsack problem consists in finding a subset of items such that the sum of their sizes is larger than or equal to a given constant and the sum of their costs is minimized. We first study a greedy-type heuristic having a worst-case bound of 2. This heuristic is then refined to obtain a new one with a worst-case bound of 3/2.

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A Cost-Aware Elasticity Provisioning System for the Cloud

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Cutting and Packing Problems: A Categorized, Application-Orientated Research Bibliography

TL;DR: All of the books and journal articles listed in the bibliography have been categorized according to the dimensionality of the problems studied and the solution methodologies employed.
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Algorithms for solving the single-sink fixed-charge transportation problem

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Kingfisher: Cost-aware elasticity in the cloud

TL;DR: Kingfisher is presented, a cost-aware system that provides efficient support for elasticity in the cloud by leveraging multiple mechanisms to reduce the time to transition to new configurations, and optimizing the selection of a virtual server configuration that minimizes the cost.
Journal ArticleDOI

Practical considerations in using model-based optimization for the scheduling and planning of batch/semicontinuous processes

TL;DR: A key point throughout the paper is the effectiveness of using multiple layers of problem representation to separate the high level problem description from its lower level mathematical models and the methods used for their solution.
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