Optimal Voltage Control in MV Network with Distributed Generation by Piotr Kacejko, Paweł Pijarski

“…The analysis carried out for random selection of independent variables, using the original heuristic algorithm, indicated a very high efficiency of the proposed control process, compared to the traditional approach. …”
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Multiobjective Reinforcement Learning Based Energy Consumption in C-RAN enabled Massive MIMO by S. Sharma, W. Yoon

“…Our proposed MORL-based Q-learning algorithm achieves superior EE performance compared with simple ON-OFF scheme and heuristic algorithms.…”
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A hybrid self-adaptive invasive weed algorithm with differential evolution by Fuqing Zhao, Songlin Du, Hao Lu, Weimin Ma, Houbin Song

“…The invasive weed algorithm (IWO) is a meta-heuristic algorithm, which is an effective and promising optimiser to address the optimisation problems. …”
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A Hybrid Adaptive Large Neighborhood Heuristic for a Real-Life Dial-a-Ride Problem by Slim Belhaiza

“…This paper tackles the DARP with time windows (DARPTW) from a new and innovative angle as it combines hybridization techniques with an adaptive large neighborhood search heuristic algorithm. The main objective is to improve the overall real-life performance of vehicle routing operations. …”
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Resilience enhancement of distribution networks based on demand response under extreme scenarios by Gang Xu, Zixuan Guo

“…In the first stage, a heuristic algorithm is introduced to determine the post‐disaster topology of the distribution network. …”
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Using Straggler Replication to Reduce Latency in Large-scale Parallel Computing by Wang, Da, Joshi, Gauri, Wornell, Gregory

“…We also propose a heuristic algorithm to search for the best replication strategies when it is difficult to model the empirical behavior of task execution time and use the proposed analysis techniques. …”
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Heuristic-based approach to customer-driven conceptual design by Chong, Yih Tng

“…This work adapts a General Best First heuristic algorithm for application on conceptual design problems. …”
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Glowworm swarm optimization (GSO) algorithm for optimization problems: a state-of-the-art review by Zainal, Nurezayana, Mohd Zain, Azlan, MohamedRadzi, Nor Haizan, Udin, Amirmudin

“…Glowworm Swarm Optimization (GSO) algorithm is a derivative-free, meta-heuristic algorithm and mimicking the glow behavior of glowworms which can efficiently capture all the maximum multimodal function. …”

Shortest path planning for single manipulator in 2D environment of deformable objects by Omar, Fakhrul Syakirin, Islam, Md. Nazrul, Haron, Habibollah

“…A heuristic algorithm to perform path planning for single manipulator in 2D environment containing deformable objects is presented. …”
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Analysis of vector evaluated particle swarm optimization guided by non-dominated solutions: Inertia weight, cognitive, and social constants by Lim, K. S., Ibrahim, Z., Buyamin, S., Ahmad, A., Shapiai, M. I., Khalil, K., Nawawi, S. W., Arshad, N. W., Naim, F.

“…Since a parameter tuning of a heuristic algorithm is normally difficult, in this paper, three important parameters of the improved VEPSO, which are inertia weight, cognitive constant, and social constant, are analyzed. …”

Job shop scheduling problem with late work criterion by Piroozfard, Hamed, Wong, Kuan Yew

“…Computational results of this probabilistic meta-heuristic algorithm were compared with a conventional genetic algorithm, and a conclusion was made based on the algorithm and problem.…”

New heuristic function in ant colony system for job scheduling in grid computing by Ku-Mahamud, Ku Ruhana, Alobaedy, Mustafa Muwafak

“…Job scheduling problem classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Ant colony system algorithm is a meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This paper focuses on enhancing the heuristic function where information about recent ants’ discoveries will be taken into account.Experiments were conducted using a simulator with dynamic environment features to mimic the grid environment.Results show that the proposed enhanced algorithm produce better output in term of utilization and make span.…”
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A Unified Strategy for Sequence and Sequence-less T-way Test Suite Generation by Abdullah, Nasser, Hujainah, Fadhl, Alsewari, Abdulrahman A., Kamal Z., Zamli

“…This paper presents a unified strategy based on the new meta-heuristic algorithm, called the Elitist Flower Pollination Algorithm (eFPA), for sequence and sequence-less coverage. …”
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Feeder delivery vehicle scheduling optimization of high-speed railway express based on trunk and branch intermodal transportation by Yao Cui, Xiaoye Zhou

“…A two-level nested heuristic algorithm with two-level coding structure is proposed to solve the problem. …”
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Multi-Strategy Improved Northern Goshawk Optimization Algorithm and Application by Fan Zhang

“…The Northern Goshawk Optimization Algorithm (NGO) is a population-based meta-heuristic algorithm inspired by the hunting behavior of the northern goshawk. …”
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A theory of multiple vehicle type dynamic marginal cost considering departure time choices by Shu-Guang Li, Qing-Hua Zhou

“…Then, the analytic expression of a multiple vehicle type dynamic marginal cost function considering departure time choices is deduced under congested and un‐congested conditions and consequently, a dynamic toll function is given. A heuristic algorithm is introduced to solve multiple vehicle type dynamic queues and toll under system optimum and user equilibrium conditions taking into account traveler's departure time. …”
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A New Hybrid Metaheuristics Algorithm for Minimizing Energy Consumption in the Flow Shop Scheduling Problem by Dana Marsetiya Utama, Dian Setiya Widodo, Wahyu Wicaksono, Leo Rizki Ardiansyah

“…We offer a new hybrid meta-heuristic algorithm for solving the problem. The paper aims to combine the cross entropy and genetic algorithm (CEGA) with the simulated annealing (SA) algorithm. …”
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Fast and computationally efficient generative adversarial network algorithm for unmanned aerial vehicle–based network coverage optimization by Marek Ružička, Marcel Vološin, Juraj Gazda, Taras Maksymyuk, Longzhe Han, MisCha Dohler

“…Considering the tremendous potential of unmanned aerial vehicles in the future, we propose a new heuristic algorithm for coverage optimization. The proposed algorithm is implemented based on a conditional generative adversarial neural network, with a unique multilayer sum-pooling loss function. …”
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Re-Aggregation Heuristics for the Large Location Problems with Lexicographic Minimax Objective by Matej Cebecauer, Lubos Buzna

“…We propose a new heuristic algorithm that provides solutions to the discrete lexicographic minimax location problem. …”
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Preventive Maintenance in Unrelated Parallel Machine Scheduling with Deterioration Effect and Setup Times by Mohammad Bagher Fakhrzad, Behnam Rajaei

“…A mathematical model is proposed and due to its complexity, a simulated annealing Mehta-heuristic algorithm is used for solving the model. Finally, numerical examples are given and sensitivity analysis with various parameters is applied to evaluate the performance of the proposed method…”
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