Computer Algorithms: Introduction to Design and Analysis
Computer Algorithms: Introduction to Design and Analysis
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Estimating High-Dimensional Directed Acyclic Graphs with the PC-Algorithm
The Journal of Machine Learning Research
Solving the one-dimensional bin packing problem with a weight annealing heuristic
Computers and Operations Research
Fast algorithms for bin packing
Journal of Computer and System Sciences
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
ISMIS'08 Proceedings of the 17th international conference on Foundations of intelligent systems
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Causal inference can be used to construct models that explain the performance of heuristic algorithms for NP-hard problems. In this paper, we show the application of causal inference to the algorithmic optimization process through an experimental analysis to assess the impact of the parameters that control the behavior of a heuristic algorithm. As a case study we present an analysis of the main parameters of one state of the art procedure for the Bin Packing Problem (BPP). The studies confirm the importance of the application of causal reasoning as a guide for improving the performance of the algorithms.