How to Solve It: Modern Heuristics

By Z. Michalewicz, David B. Fogel. 2000

2,291 citations recorded by the source corpus.

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Citations in the corpus

Trend analysis of climate time series: A review of methods (2019, methodology): “This is technically challenging and likely necessitates the implementation of advanced optimization techniques, such as genetic algorithms (Michalewicz and Fogel, 2000).”
USPEX - Evolutionary crystal structure prediction (2006, unknown): “Quoting from Michalewicz and Fogel [13]:”
Differential Evolution Using a Neighborhood-Based Mutation Operator (2009, unknown): “[31] proposed a hybridization of DE with the Neighborhood Search (NS), which appears as a main strategy underpinning Evolutionary Programming (EP) [32].”
Adaptive game AI with dynamic scripting (2006, background): “According to Michalewicz and Fogel (2000), the two main factors of importance when attempting to achieve high performance for a learning mechanism are the exclusion of randomness and the addition of domain-speciﬁc knowledge.”
Planning and scheduling in the process industry (2002, background): “If CP also fails, the last resort might be to use heuristic approaches [48], e.”
Artificial intelligence in supply chain management: theory and applications (2010, methodology): “Fuzzy logic has also been applied to solve the well-known traveling salesman problem (TSP) in a SC setting (Michalewicz and Fogel 2000).”
Factors associated with clinical trials that fail and opportunities for improving the likelihood of success: A review (2018, unknown): “, a Valuated State Space [87]) for trading off degrees of achievement in various parameters can offer a quantitative measure for comparing alternative choices.”
Benchmark Functions for the CEC'2013 Special Session and Competition on Large-Scale Global Optimization (2008, methodology): “1 Introduction Numerous metaheuristic algorithms have been successfully applied to many optimization problems [1, 2, 5, 9, 10, 15, 16, 17, 21, 35, 39].”
Bayesian Networks and Decision Graphs (2001, unknown): “Olmsted (1983) and Shachter (1986) introduced arc-reversal, and Shenoy (1992), Jensen et al.”
A flexible computational framework for detecting, characterizing, and interpreting statistical patterns of epistasis in genetic studies of human disease susceptibility. (2006, methodology): “For example, once a new attribute is constructed with MDR it can be added back to the attribute list and the full dataset analysed using any classifier combined with a deterministic search algorithm such as best-first (Michalewicz and Fogel, 2000) or a stochastic search algorithm such as simulated a”