2008 Eighth International Conference on Hybrid Intelligent Systems 2008
DOI: 10.1109/his.2008.71
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Solving an Open Shop Scheduling Problem by a Novel Hybrid Multi-Objective Ant Colony Optimization

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Cited by 6 publications
(4 citation statements)
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“…V. dubia invasion across the Blue Mountains Ecoregion and prioritize treatments at early stages in the invasion process when eradication is most likely (Harvey and Mazzotti, 2014 and Vitousek, 1992). Prior to invasion, fuel-limited forest scablands served as natural fire breaks, increasing burn heterogeneity throughout the larger forested landscape.…”
Section: Management Implicationsmentioning
confidence: 99%
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“…V. dubia invasion across the Blue Mountains Ecoregion and prioritize treatments at early stages in the invasion process when eradication is most likely (Harvey and Mazzotti, 2014 and Vitousek, 1992). Prior to invasion, fuel-limited forest scablands served as natural fire breaks, increasing burn heterogeneity throughout the larger forested landscape.…”
Section: Management Implicationsmentioning
confidence: 99%
“…Over the past century, non-native annual grass invasions have transformed the American West. Throughout much of the Great Basin, southwestern deserts, and Californian Mediterranean regions, non-native annual grasses have initiated grass-fire cycles that have converted invaded shrublands to annual grasslands, altering community dynamics, hydrologic and nutrient cycling, reducing livestock forage, and increasing fire frequency and extent (Mack, 1981;D'Antonio and Vitousek, 1992;Brooks et al, 2004Brooks et al, , 2016Fusco et al, 2019). In contrast, many…”
Section: Introductionmentioning
confidence: 99%
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“…This model seeks to minimize the mean tardiness and the mean completion time. Panahi and Tavakkoli-Moghaddam (2011) proposed a hybrid method based on multi-objective simulated annealing (SA) and ant colony optimization (ACO) to solve an open shop scheduling problem that minimizes biobjectives, namely makespan and total tardiness. They compared their computational results with a well-known multi-objective genetic algorithm, namely NSGA II.…”
Section: Introductionmentioning
confidence: 99%