[PDF] Top 20 A tensor based selection hyper heuristic for cross domain heuristic search
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A tensor based selection hyper heuristic for cross domain heuristic search
... Monte-Carlo based move acceptance strategy [7], Simulated Annealing [10], Late Acceptance [11], there is strong empirical evidence that combining simple components under a selection ... See full document
47
A case study of controlling crossover in a selection hyper heuristic framework using the multidimensional knapsack problem
... each hyper-heuristic is sufficient as these instances are extremely ...the hyper-heuristics with average performance over 10 runs ...Strategy-based hyper-heuristics as suggested by ... See full document
31
A learning automata based multiobjective hyper heuristic
... particular domain by experts, have been successfully applied to many computationally hard optimisation ...problem domain or a slight change in the problem description would often require additional expert ... See full document
15
A multi objective hyper heuristic based on choice function
... own. Hyper-heuristic frameworks, generally, impose a domain barrier which separates the hyper-heuristic from the domain implementation along with low level heuristics to provide ... See full document
51
A Hidden Markov Model Approach to the Problem of Heuristic Selection in Hyper Heuristics with a Case Study in High School Timetabling Problems
... sequence-based selection hyper-heuristic is presented that produces excellent results on a suite of high school timetabling prob- ...sequence-based selection ... See full document
30
A software interface for supporting the application of data science to optimisation
... on selection hyper-heuristics which mix and control a pre- defined set of low level heuristics during the search process ...first Cross-domain Heuristic Search ... See full document
6
Improving performance of a hyper heuristic using a multilayer perceptron for vehicle routing
... effective heuristic optimisa- tion methods to real-world problems is often time-consuming and becoming increasingly ...of heuristic search methods and obtaining more general approaches applicable to ... See full document
8
An apprenticeship learning hyper heuristic for vehicle routing in HyFlex
... Adaptive Hyper- Heuristic (AdapHH) is a multi-phase learning hyper-heuristic ...each heuristic is applied is also dynamically determined during the ...low-level heuristic are ... See full document
8
A stochastic local search algorithm with adaptive acceptance for high school timetabling
... adaptive search procedure (GRASP) heuristic to solve a Brazilian high school timetabling ...algorithm based hyper-heuristic selection ...local search heuristics with ... See full document
18
Performance of selection hyper heuristics on the extended HyFlex domains
... acceptance-based hyper-heuristic (F-LAHH) [8] was implemented for solving MAX-SAT problems and showed promising ...proportionate selection mechanism (RUA1-F1FPS) [7] for the heuristic ... See full document
9
Learning heuristic selection using a time delay neural network for open vehicle routing
... generation hyper-heuristic for VRP in the HyFlex framework ...pert selection hyper-heuristic through training how to perform heuristic selection using a set of sample ... See full document
8
An advanced IWD based Hyper heuristic workflow scheduling in computational grid
... Description: Once the resources are initialized both statically and dynamically, the Intelligent Water Drops are randomly spread over the resources. The associated water drops with in a coverage area forms the cluster ... See full document
6
A tensor based hyper heuristic for nurse rostering
... advantages based on which the latter method is favoured over the former ...The tensor-based hyper-heuristic in this paper uses the scores achieved after factorization to rank ... See full document
39
Machine Learning Based Heuristic Search Algorithms to Solve Birds of a Feather Card Game
... The combination of heuristic search and DFS was im- plemented because the benefit of the heuristic models di- minished with a lower amount of cards. Tables 3 and 4 list the correspondence between ... See full document
6
Searching the hyper heuristic design space
... tabu search ([8], [9]) and adaptive penalties ...quent search process. Examples of offline learning for hyper-heuristics includes learning-classifier systems [11], case-based reasoning [12] and ... See full document
9
ANALYSIS OF DIVIDE-AND CONQUER LOCAL SEARCH HEURISTICS WITH QUADRANT AND NEIGHBOR RESTRICTIONS
... For DACQ, we restrict a point to the quadrant in which it is assigned initially. When a lattice point is divided into four new points, we consider only movements of currently assigned points to one of the four new ... See full document
9
Few heuristic optimization algorithms to solve the multi-period fixed charge production-distribution problem
... inventories in the distribution channel. As a result of this pressure, many companies are exploring closer coordination along the manufacturing/ distribution channel [2]. Many companies strive to synchronize their ... See full document
11
Application of Artificial Immune System Algorithm to Electromagnetics Problems
... is based on the evolution theory and survival of the ...their search for the best location in a field is ...they search for the best location based on the collective intelligence of the swarm ... See full document
17
Cube Pruning as Heuristic Search
... A* search with inadmissible ...the search space becomes so large that brute-force item generation is much too slow to be practi- ...the heuristic search framework we may ask the question: is ... See full document
10
Planning For Non-Player Characters By Learning From Demonstration
... the search completes in the same number of ...T-Graph heuristic visits each T- Graph edge once per heuristic request, so for searches with the same number of expansions, we expect a linear increase ... See full document
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