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558. Hybrid Genetic Algorithm for Solving The Three-index Assignment Problem
Invited abstract in session WC-52: Heuristic Algorithms for Combinatorial Optimization Problems I (Contributed), stream Combinatorial Optimization.
Wednesday, 12:30-14:00Room: 8003 (building: 202)
Authors (first author is the speaker)
| 1. | Mohamed Mehbali
|
| Centre for Research Informed Teaching, London South Bank University |
Abstract
The paper introduces the three-index assignment problem (3IAP) consists of assigning n tasks to n machines in n factories provided that a task is exactly allocated to a machine in a factory so that the total cost of allocation is minimal. The 3IAP, extending the classic two-dimensional assignment problem, is established as NP-hard. Due to its computational complexity, innovative heuristics are designed for near-optimal solutions. Applying Genetic Algorithms (GA) to 3IAP evolves a population, seeking optimal or near-optimal solutions over generations. This investigation advocates enhancing their quality by integrating a local search method.
The study proposes a hybrid genetic algorithm, integrating GA with a particular local search based on permutations, yielding high-quality solutions in a notably reduced computational timeframe compared to deterministic methods. The efficacy of this hybrid approach is demonstrated through experimental results and comparisons with other optimisation methodologies.
Keywords
- Algorithms
- Combinatorial Optimization
- Programming, Integer
Status: accepted
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