The Accuracy of Search Heuristics: An Empirical Study on Knapsack Problems
نویسندگان
چکیده
Theoretical models for the evaluation of quickly improving search strategies, like limited discrepancy search, are based on specific assumptions regarding the probability that a value selection heuristic makes a correct prediction. We provide an extensive empirical evaluation of value selection heuristics for knapsack problems. We investigate how the accuracy of search heuristics varies as a function of depth in the search-tree, and how the accuracies of heuristic predictions are affected by the relative strength of inference methods like pruning and constraint propagation.
منابع مشابه
Generation Methods for Multidimensional Knapsack Problems and their Implications
Although there are a variety of heuristics developed and applied to the variants of the binary knapsack problem, the testing of these heuristics are based on poorly defined test problems. This paper reviews the various types of knapsack problems, considers how test problems have been generated and depicts via empirical results the implications of using poorly formed test problems for empirical ...
متن کاملInconsistency and Accuracy of Heuristics with A* Search
Many studies in heuristic search suggest that the accuracy of the heuristic used has a positive impact on improving the performance of the search. In another direction, historical research perceives that the performance of heuristic search algorithms, such as A* and IDA*, can be improved by requiring the heuristics to be consistent – a property satisfied by any perfect heuristic. However, a few...
متن کاملNeural, Genetic, And Neurogenetic Approaches For Solving The 0-1 Multidimensional Knapsack Problem
The multi-dimensional knapsack problem (MDKP) is a well-studied problem in Decision Sciences. The problem’s NP-Hard nature prevents the successful application of exact procedures such as branch and bound, implicit enumeration and dynamic programming for larger problems. As a result, various approximate solution approaches, such as the relaxation approaches, heuristic and metaheuristic approache...
متن کاملPerformance of Selection Hyper-heuristics on the Extended HyFlex Domains
Selection hyper-heuristics perform search over the space of heuristics by mixing and controlling a predefined set of low level heuristics for solving computationally hard combinatorial optimisation problems. Being reusable methods, they are expected to be applicable to multiple problem domains, hence performing well in cross-domain search. HyFlex is a general purpose heuristic search API which ...
متن کاملA dynamic programming approach for solving nonlinear knapsack problems
Nonlinear Knapsack Problems (NKP) are the alternative formulation for the multiple-choice knapsack problems. A powerful approach for solving NKP is dynamic programming which may obtain the global op-timal solution even in the case of discrete solution space for these problems. Despite the power of this solu-tion approach, it computationally performs very slowly when the solution space of the pr...
متن کامل