A hybrid scatter search/electromagnetism meta-heuristic for project scheduling
TLDR
This paper combines elements from scatter search, a generic population-based evolutionary search method, and a recently introduced heuristic method for the optimisation of unconstrained continuous functions based on an analogy with electromagnetism theory to provide near-optimal heuristic solutions for resource-constrained project scheduling.About:
This article is published in European Journal of Operational Research.The article was published on 2006-03-01 and is currently open access. It has received 332 citations till now. The article focuses on the topics: Heuristic & Heuristics.read more
Citations
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35 years of studies on business failure: an overview of the classic statistical methodologies and their related problems
Sofie Balcaen,Hubert Ooghe +1 more
TL;DR: This paper extensively elaborates on the application of (1) univariate analysis, (2) risk index models, (3) multivariate discriminant analysis, and (4) conditional probability models, such as logit, probit and linear probability models.
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Experimental investigation of heuristics for resource-constrained project scheduling: An update
Rainer Kolisch,Sönke Hartmann +1 more
TL;DR: In this paper, a survey of heuristics for resource-constrained project scheduling problem (RCPSP) is presented, which provides an update of our survey which was published in 2000.
Experimental Investigation of Heuristics for Resource-Constrained Project Scheduling: An Update
Rainer Kolisch,Sönke Hartmann +1 more
TL;DR: In this paper, a survey of heuristics for resource-constrained project scheduling problem (RCPSP) is presented, which provides an update of our survey which was published in 2000.
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Biased random-key genetic algorithms for combinatorial optimization
TL;DR: This paper presents a tutorial on the implementation and use of biased random-key genetic algorithms for solving combinatorial optimization problems, illustrating the ease in which sequential and parallel heuristics based on biased Random-Key genetic algorithms can be developed.
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Predicting customer retention and profitability by using random forests and regression forests techniques
Bart Larivière,Dirk Van den Poel +1 more
TL;DR: The research findings demonstrate that both random forests techniques provide better fit for the estimation and validation sample compared to ordinary linear regression and logistic regression models, and suggest that past customer behavior is more important to generate repeat purchasing and favorable profitability evolutions.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Genetic algorithms in search, optimization and machine learning
TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
Journal ArticleDOI
Resource-constrained project scheduling: Notation, classification, models, and methods
TL;DR: A classification scheme is provided, i.e. a description of the resource environment, the activity characteristics, and the objective function, respectively, which is compatible with machine scheduling and which allows to classify the most important models dealt with so far, and a unifying notation is proposed.
Journal ArticleDOI
Scheduling subject to resource constraints: classification and complexity
TL;DR: In this article, an extension of deterministic sequencing and scheduling problems, in which the jobs require the use of additional scarce resources during their execution, is considered, and a classification scheme for resource constraints is proposed and the computational complexity of the extended problem class is investigated.
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Experimental investigation of heuristics for resource-constrained project scheduling: An update
Rainer Kolisch,Sönke Hartmann +1 more