A Hybrid Coral Reefs Optimization—Variable Neighborhood Search Approach for the Unequal Area Facility Layout Problem

García-Hernández, Laura; Salas-Morera, Lorenzo; Carmona-Muñoz, Carlos; Abraham, Ajith; Salcedo‐Sanz, Sancho

doi:10.1109/access.2020.3010577

Cited by 12 publications

(6 citation statements)

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“…The Coral Reefs Optimization algorithm (CRO) is a type of evolutionary technique proposed in [34,35] that has been successfully applied in several optimization problems [36][37][38][39][40][41][42]. The CRO uses a n × m grid R (i.e., the coral reef), where each square (denoted by its coordinates (i,j)) can host a candidate solution to the problem x (i.e., a coral).…”

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

confidence: 99%

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

et al. 2021

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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.

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

confidence: 99%

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

et al. 2021

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“…The cross-segment logistics are first disposed to the transfer station and then transported to the destination using the AGV within the segment. The general problem is known to be NP-hard [23]. To solve the problem in an acceptable time, a hybrid approach combining the non-dominated sorting genetic algorithm-II (NSGA-II) with tabu search (TS) is adopted.…”

Section: Introductionmentioning

confidence: 99%

Bi-Objective Optimization for Multi-Row Facility Layout Problem Integrating Automated Guided Vehicle Path

2023

IEEE Access

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For machining workshops that use automated guided vehicles (AGVs) for material handling and management, workstation layout and AGV path are coupling factors affecting the material handling cost (MHC). The multi-row layout is a typical pattern in many machining workshops, and currently, there is a lack of studies on the multi-row layout problem (MRLP) while taking into account the AGV path. This study established a bi-objective multi-row layout optimization methodology integrating the AGV path to minimize MHC and area occupancy. Specifically, workstations and transfer stations were arranged in the workshop following several non-intersecting AGV paths to decrease the material handling distance between workstations. First, a multi-row layout optimization model was established. Second, a hybrid approach combining the non-dominated sorting genetic algorithm-II (NSGA-II) and tabu search (TS) was proposed to solve it. The effectiveness of the proposed model was verified in the practice of a structural components machining workshop, and the results were compared with that of a loop-based layout. In addition, the proposed approach was compared with an exact approach and another hybrid approach based on a genetic algorithm (GA) and simulated annealing (SA). The experimental results showed that the proposed approach was able to achieve better sets of Pareto solutions within reasonable computational time. INDEX TERMSFacility layout problem, bi-objective optimization, multi-row layout, automated guided vehicle path. ABBREVIATIONS FLP Facility layout problem. MHC Material handling cost. SRLP Single-row layout problem. DRLP Double-row layout problem. MRLP Multi-row layout problem. AGV Automatic guided vehicle. NSGA-II Non-dominated sorting genetic algorithm-II. TS Tabu search. FMS Flexible manufacturing system. GA Genetic algorithm.The associate editor coordinating the review of this manuscript and approving it for publication was Roberto Sacile .

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“…Many of the heuristic approaches are prone to fall into local optimum. To deal with it, Garcia-Hernandez et al [36] developed a CRO-VNS algorithm, that hybridizes the coral reefs optimization algorithm with variable neighborhood search and reached better solutions than the previous algorithms. Then, the CSE algorithm has been developed with the aim of enhancing the efficiency of resolving multi-objective layout optimization problems by effectively finding the Pareto optimal solution [37].…”

Section: Introductionmentioning

confidence: 99%

Efficient Approaches for Layout Problems of Large Chemical Plants Based on MILP Model

Zhou

et al. 2023

Processes

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This paper presents two novel solution approaches for addressing large-scale multi-floor process plant layout problems. Based on the mixed integer linear programming (MILP) model, the first solution approach employs a multi-directional search strategy while the second improves solution efficiency by reducing model size through an iterative framework. Both approaches determine the spatial arrangement of the plant equipment considering equipment-floor allocation, non-overlapping constraints, tall equipment penetrating multiple floors, etc. The computational results indicate that the proposed approaches achieved potential cost savings for four illustrative examples when compared to the previous studies. Finally, engineering experience constraints were included to represent a more complex industrial situation, and their applicability was tested with the last example.

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A Hybrid Coral Reefs Optimization—Variable Neighborhood Search Approach for the Unequal Area Facility Layout Problem

Cited by 12 publications

References 61 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

Bi-Objective Optimization for Multi-Row Facility Layout Problem Integrating Automated Guided Vehicle Path

Efficient Approaches for Layout Problems of Large Chemical Plants Based on MILP Model

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