RECORD
A hybrid Benders decomposition and bees algorithm matheuristic approach to transmission expansion planning considering energy storage
Optimization and Control · Submitted 4 Mar 2019
abstract compiled · 2026-09-23 · no language-model review
The authors' main claim The BBHA is shown to be highly effective hybrid matheuristic algorithm that performs at least as well as either Benders decomposition or the Bees Algorithm where these are effective on their own, and significantly improves upon the individual approaches where neither component part has a pronounced advantage.
The compiled record
The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.
Open the compiled record
The abstract, sentence by sentence
This paper introduces a novel hybrid optimisation algorithm that combines elements of both metaheuristic search and integer programming. This new matheuristic combines elements of Benders decomposition and the Bees Algorithm, to create the Bee-Benders Hybrid Algorithm (BBHA) which retains many of the advantages both of the methods. Specifically it is designed to be easily parallelizable, to produce good solutions quickly while still retaining a guarantee of optimality when run for a sufficiently long time. The algorithm is tested using a transmission network expansion and energy storage planning model, a challenging and very large scale mixed integer linear programming problem. Transmission network planning problems are already difficult on their own. When including the planning for storage systems in the network, the variation of demand over time has to be taken into account significantly increasing the size and difficulty of the optimization problem. The BBHA is shown to be highly effective hybrid matheuristic algorithm that performs at least as well as either Benders decomposition or the Bees Algorithm where these are effective on their own, and significantly improves upon the individual approaches where neither component part has a pronounced advantage. While the paper demonstrates the effectiveness in terms of the concrete electricity network planning problem, the algorithm could be readily applied to any mixed integer linear program, and is expected to work particularly well whenever this has a structure that is amenable to Benders decomposition.
background contribution method result interpretation main claim
| # | sentence | role | the authors' own work | states the main conclusion | strength |
|---|---|---|---|---|---|
| s0 | This paper introduces a novel hybrid optimisation algorithm that combines elements of both metaheuristic search and integer programming. | contribution 0.99 | 0.87 | 0.06 | asserted 1.00 |
| s1 | This new matheuristic combines elements of Benders decomposition and the Bees Algorithm, to create the Bee-Benders Hybrid Algorithm (BBHA) which retains many of the advantages both of the methods. | contribution 0.65 | 0.89 | 0.08 | asserted 1.00 |
| s2 | Specifically it is designed to be easily parallelizable, to produce good solutions quickly while still retaining a guarantee of optimality when run for a sufficiently long time. | contribution 0.51 | 0.55 | 0.07 | asserted 0.99 |
| s3 | The algorithm is tested using a transmission network expansion and energy storage planning model, a challenging and very large scale mixed integer linear programming problem. | method 0.83 | 0.86 | 0.04 | asserted 0.99 |
| s4 | Transmission network planning problems are already difficult on their own. | background 1.00 | 0.07 | 0.02 | asserted 1.00 |
| s5 | When including the planning for storage systems in the network, the variation of demand over time has to be taken into account significantly increasing the size and difficulty of the optimization problem. | background 1.00 | 0.16 | 0.02 | asserted 1.00 |
| s6 | The BBHA is shown to be highly effective hybrid matheuristic algorithm that performs at least as well as either Benders decomposition or the Bees Algorithm where these are effective on their own, and significantly improves upon the individual approaches where neither component part has a pronounced advantage. | result 0.98 | 0.93 | 0.80 | asserted 1.00 |
| s7 | While the paper demonstrates the effectiveness in terms of the concrete electricity network planning problem, the algorithm could be readily applied to any mixed integer linear program, and is expected to work particularly well whenever this has a structure that is amenable to Benders decomposition. | interpretation 0.83 | 0.29 | 0.12 | hedged possibility 0.96 |
What was examined, and what was not
- arXiv listing abstract v2
- full text
- figures and tables
- references and citing sentences
- relations to other papers
- P abstract
- S sections
- T body sentences
- C citations
- R cross-paper relations
The paper
Original abstract
This paper introduces a novel hybrid optimisation algorithm that combines elements of both metaheuristic search and integer programming. This new matheuristic combines elements of Benders decomposition and the Bees Algorithm, to create the Bee-Benders Hybrid Algorithm (BBHA) which retains many of the advantages both of the methods. Specifically it is designed to be easily parallelizable, to produce good solutions quickly while still retaining a guarantee of optimality when run for a sufficiently long time. The algorithm is tested using a transmission network expansion and energy storage planning model, a challenging and very large scale mixed integer linear programming problem. Transmission network planning problems are already difficult on their own. When including the planning for storage systems in the network, the variation of demand over time has to be taken into account significantly increasing the size and difficulty of the optimization problem. The BBHA is shown to be highly effective hybrid matheuristic algorithm that performs at least as well as either Benders decomposition or the Bees Algorithm where these are effective on their own, and significantly improves upon the individual approaches where neither component part has a pronounced advantage. While the paper demonstrates the effectiveness in terms of the concrete electricity network planning problem, the algorithm could be readily applied to any mixed integer linear program, and is expected to work particularly well whenever this has a structure that is amenable to Benders decomposition.
Human review
Discussion
Know something about this paper? Leave a comment, or highlight any passage above to comment on it.