Addressing Unequal Area Facility Layout Problems with the Coral Reef Optimization algorithm with Substrate Layers

García-Hernández, Laura; García‐Hernández, Jorge; Salas-Morera, Lorenzo; Carmona-Muñoz, Carlos; Alghamdi, Norah Saleh; Oliveira, José Valente de; Salcedo‐Sanz, Sancho

doi:10.1016/j.engappai.2020.103697

Cited by 20 publications

(11 citation statements)

References 60 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…On the other hand, the Coral Reefs Optimization with Substrate Layer algorithm (CRO-SL) [29,45] is a multi-method ensemble based on in the standard CRO algorithm, yet with a structure that promotes competitive co-evolution using the layers deployed. Each layer proposed implements a different search strategy, operator, constraint, repairing function, etc., although the use of diverse search operators is the most common mechanism for the CRO-SL.…”

Section: Evolutionary Meta-heuristic Proposed: the Coral Reefs Optimization Algorithmmentioning

confidence: 99%

“…Conceptually, the CRO is an evolutionary-type (meta-heuristic) algorithm that is based on the concept of reproductive behavior of corals on real coral reefs. This algorithm can be considered to be a mix of the Simulate Annealing and Evolutionary algorithms [29]. The CRO algorithm proposed in this work can be tested with different search operators, as exploration mechanisms, obtaining this a powerful evolutionary-like algorithm for solving optimization problems.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimal Generation Scheduling in Hydro-Power Plants with the Coral Reefs Optimization Algorithm

et al. 2021

View full text Add to dashboard Cite

Hydro-power plants are able to produce electrical energy in a sustainable way. A known format for producing energy is through generation scheduling, which is a task usually established as a Unit Commitment problem. The challenge in this process is to define the amount of energy that each turbine-generator needs to deliver to the plant, to fulfill the requested electrical dispatch commitment, while coping with the operational restrictions. An optimal generation scheduling for turbine-generators in hydro-power plants can offer a larger amount of energy to be generated with respect to non-optimized schedules, with significantly less water consumption. This work presents an efficient mathematical modelling for generation scheduling in a real hydro-power plant in Brazil. An optimization method based on different versions of the Coral Reefs Optimization algorithm with Substrate Layers (CRO) is proposed as an effective method to tackle this problem. This approach uses different search operators in a single population to refine the search for an optimal scheduling for this problem. We have shown that the solution obtained with the CRO using Gaussian search in exploration is able to produce competitive solutions in terms of energy production. The results obtained show a huge savings of 13.98 billion (liters of water) monthly projected versus the non-optimized scheduling.

show abstract

Section: Evolutionary Meta-heuristic Proposed: the Coral Reefs Optimization Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Generation Scheduling in Hydro-Power Plants with the Coral Reefs Optimization Algorithm

et al. 2021

View full text Add to dashboard Cite

show abstract

“…By assuming floor space larger than the sum of all facilities’ area, the problem gets simplified. But the simplification makes the facilities to get clustered towards the centre of the plant (Montreuil, 1991; Meller et al , 1998; Sherali et al , 2003; Montreuil et al , 2004; Jankovits et al , 2011; Bozer and Wang, 2012; Gonçalves and Resende, 2015; Xiao et al , 2016; Paes et al , 2017; Garcia-Hernandez et al , 2020). Many heuristics have been developed to solve the MIP model of Montreuil (1991).…”

Section: Continuous Space Facility Layout Problemsmentioning

confidence: 99%

“…Further, the SA algorithm application is made to search the larger solution space for improvement of solution quality. More recently, Garcia-Hernandez et al (2020) developed a method to do several searching procedures over a single population at the same time. Authors named this meta-heuristic approach as Coral Reefs Optimization algorithm with Substrate Layers (CRO-SL).…”

Section: Continuous Space Facility Layout Problemsmentioning

confidence: 99%

A survey on discrete space and continuous space facility layout problems

Hunagund¹,

Pillai

Kempaiah

2021

JFM

View full text Add to dashboard Cite

Purpose The purpose of this paper is to review, evaluate and classify the academic research that has been published in facility layout problems (FLPs) and to analyse how researches and practices on FLPs are. Design/methodology/approach The review is based on 166 papers published from 1953 to 2021 in international peer-reviewed journals. The literature review on FLPs is presented under broader headings of discrete space and continuous space FLPs. The important formulations of FLPs under static and dynamic environments represented in the discrete and continuous space are presented. The articles reported in the literature on various representations of facilities for the continuous space Unequal Area Facility Layout Problems (UA-FLPs) are summarized. Discussed and commented on adaptive and robust approaches for dynamic environment FLPs. Highlighted the application of meta-heuristic solution methods for FLPs of a larger size. Findings It is found that most of the earlier research adopted the discrete space for the formulation of FLPs. This type of space representation for FLPs mostly assumes an equal area for all facilities. UA-FLPs represented in discrete space yield irregular shape facilities. It is also observed that the recent works consider the UA-FLPs in continuous space. The solution of continuous space UA-FLPs is more accurate and realistic. Some of the recent works on UA-FLPs consider the flexible bay structure (FBS) due to its advantages over the other representations. FBS helps the proper design of aisle structure in the detailed layout plan. Further, the recent articles reported in the literature consider the dynamic environment for both equal and unequal area FLPs to cope with the changing market environment. It is also found that FLPs are Non-deterministic Polynomial-complete problems, and hence, they set the challenges to researchers to develop efficient meta-heuristic methods to solve the bigger size FLPs in a reasonable time. Research limitations/implications Due to the extremely large number of papers on FLPs, a few papers may have inadvertently been missed. The facility layout design research domain is extremely vast which covers other areas such as cellular layouts, pick and drop points and aisle structure design. This research review on FLPs did not consider the papers published on cellular layouts, pick and drop points and aisle structure design. Despite the possibility of not being all-inclusive, the authors firmly believe that most of the papers published on FLPs are covered and the general picture presented on various approaches and parameters of FLPs in this paper are precise and trustworthy. Originality/value To the best of the authors’ knowledge, this paper reviews and classifies the literature on FLPs for the first time under the broader headings of discrete space and continuous space representations. Many important formulations of FLPs under static and dynamic environments represented in the discrete and continuous space are presented. This paper also provides the observations from the literature review and identifies the prospective future directions.

show abstract

“…Firstly, García-Hernández et al [48] put into practice a basic CRO algorithm applied to the UA-FLP, improving the solutions previously found in a wellknown set of problems. This basic CRO was subsequently improved by means of an island evolution model [49] and a combined evolution model called a Substrate Layers model CRO (CRO-SL) [50]. Recently, a multi-objective interactive CRO algorithm has been developed to take into account the subjective preferences of an expert designer [10].…”

Section: Introductionmentioning

confidence: 99%

A Multi-User Interactive Coral Reef Optimization Algorithm for Considering Expert Knowledge in the Unequal Area Facility Layout Problem

Salas-Morera¹,

García-Hernández²,

Carmona-Muñoz³

2021

Applied Sciences

View full text Add to dashboard Cite

The problem of Unequal Area Facility Layout Planning (UA-FLP) has been addressed by a large number of approaches considering a set of quantitative criteria. Moreover, more recently, the personal qualitative preferences of an expert designer or decision-maker (DM) have been taken into account too. This article deals with capturing more than a single DM’s personal preferences to obtain a common and collaborative design including the whole set of preferences from all the DMs to obtain more complex, complete, and realistic solutions. To the best of our knowledge, this is the first time that the preferences of more than one expert designer have been considered in the UA-FLP. The new strategy has been implemented on a Coral Reef Optimization (CRO) algorithm using two techniques to acquire the DMs’ evaluations. The first one demands the simultaneous presence of all the DMs, while the second one does not. Both techniques have been tested over three well-known problem instances taken from the literature and the results show that it is possible to obtain sufficient designs capturing all the DMs’ personal preferences and maintaining low values of the quantitative fitness function.

show abstract

Addressing Unequal Area Facility Layout Problems with the Coral Reef Optimization algorithm with Substrate Layers

Cited by 20 publications

References 60 publications

Optimal Generation Scheduling in Hydro-Power Plants with the Coral Reefs Optimization Algorithm

Optimal Generation Scheduling in Hydro-Power Plants with the Coral Reefs Optimization Algorithm

A survey on discrete space and continuous space facility layout problems

A Multi-User Interactive Coral Reef Optimization Algorithm for Considering Expert Knowledge in the Unequal Area Facility Layout Problem

Contact Info

Product

Resources

About