Bacterial foraging optimisation: Nelder-Mead hybrid algorithm for economic load dispatch

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Nonconvex Economic Dispatch With AC Constraints by a New Real Coded Genetic Algorithm (2009, methodology): “The data of this test system are mainly derived from [1] and [32] and the maximum spinning reserve capacity of six out of ten units (the units without POZ) is set at 15%–30% of the maximum output power [37].”
Economic Load Dispatch—A Comparative Study on Heuristic Optimization Techniques With an Improved Coordinated Aggregation-Based PSO (2009, methodology): “In the literature there are many HOTs applications in this system [2], [4], [5],”
Continuous quick group search optimizer for solving non-convex economic dispatch problems (2012, methodology): “These results are compared ith particle swarm optimization (PSO) [17], genetic algorithm GA) [17], multiple Tabu search (MTS) algorithm [35], new paricle swarm optimization with local random search (NPSO-LRS) 5], bacterial foraging optimization (BFO) [7], new adaptive paricle swarm optimization (NAP”
Iteration PSO with time varying acceleration coefficients for solving non-convex economic dispatch problems (2012, methodology): “[35], new adaptive PSO (NAPSO) algorithm [36], self-organizing hierarchical PSO (SOH-PSO) method [27], hybrid harmony search (HHS) method [37], GA [33], PSO [33] and Iteration PSO (IPSO) [29] in Table 1.”