Dynamic Solution Probability Acceptance within the Flower Pollination Algorithm for t-way Test Suite Generation
arXiv:1902.11160
Abstract
Flower Pollination Algorithm (FPA) is the new breed of metaheuristic for the general optimization problem. In this paper, an improved algorithm based on Flower Pollination Algorithm (FPA), called imFPA, has been proposed. In imFPA, the static selection probability is replaced by the dynamic solution selection probability in order to enhance the diversification and intensification of the overall search process. Experimental adoptions on combinatorial t- way test suite generation problem (where t indicates the interaction strength) show that imFPA produces very competitive results as compared to existing strategies.
IIC 2018 Conference Accepted
References in corpus (3)
- Achievement of Minimized Combinatorial Test Suite for Configuration-Aware Software Functional Testing Using the Cuckoo Search Algorithm
- A Hybrid Q-Learning Sine-Cosine-based Strategy for Addressing the Combinatorial Test Suite Minimization Problem
- Fuzzy adaptive teaching learning-based optimization strategy for the problem of generating mixed strength t-way test suites