Article detail · 2013
An artificial bee colony algorithm for the economic lotscheduling problem
- Year
- 2013
- Type
- article
Data source split
- YÖKSİS YÖKSİS article record
- YÖKSİS venue International Journal of Production Research
- Catalog match (ISSN) International Journal of Production Research
- OpenAlex OpenAlex enrichment (abstract, citations, topics)
Abstract
OpenAlex · English
In this study, we present an artificial bee colony (ABC) algorithm for the economic lot scheduling problem modelled through the extended basic period (EBP) approach. We allow both power-of-two (PoT) and non-power-of-two multipliers in the solution representation. We develop mutation strategies to generate neighbouring food sources for the ABC algorithm and these strategies are also used to develop two different variable neighbourhood search algorithms to further enhance the solution quality. Our algorithm maintains both feasible and infeasible solutions in the population through the use of some sophisticated constraint handling methods. Experimental results show that the proposed algorithm succeeds to find the all the best-known EBP solutions for the high utilisation 10-item benchmark problems and improves the best known solutions for two of the six low utilisation 10-item benchmark problems. In addition, we develop a new problem instance with 50 items and run it at different utilisation levels ranging from 50 to 99% to see the effectiveness of the proposed algorithm on large instances. We show that the proposed ABC algorithm with mixed solution representation outperforms the ABC that is restricted only to PoT multipliers at almost all utilisation levels of the large instance.
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Citations
OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.
27 citations
OpenAlex cited_by_count (cache / database)
9 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).
- An energy-efficient bi-objective no-wait permutation flowshop scheduling problem to minimize total tardiness and total energy consumption 2020
- A Novel Neural Network Training Algorithm for the Identification of Nonlinear Static Systems: Artificial Bee Colony Algorithm Based on Effective Scout Bee Stage 2021
- A Novel Neural Network Training Algorithm for the Identification of Nonlinear Static Systems: Artificial Bee Colony Algorithm Based on Effective Scout Bee Stage 2021
- Distance-Constrained Vehicle Routing Problems: A Case Study Using Artificial Bee Colony Algorithm 2020
- A review on the versions of artificial bee colony algorithm for scheduling problems 2025
- A review on the versions of artificial bee colony algorithm for scheduling problems 2025
- A discrete artificial bee colony algorithm for the Economic Lot Scheduling problem with returns 2014
- Artificial Bee Colony Algorithm for Labor Intensive Project Type Job Shop Scheduling Problem: A Case Study 2019
- Modified Artificial Bee Colony Algorithm for Sizing Optimization of Truss Structures 2021