scholarly journals Hybrid method for solving the non smooth cost function economic dispatch problem

2020 ◽  
Vol 10 (1) ◽  
pp. 609
Author(s):  
Wanchai Khamsen ◽  
Chiraphon Takeang ◽  
Patiphat Aunban
Keyword(s):  
Cost Function ◽  
Hybrid Method ◽  
Search Algorithm ◽  
Economic Dispatch ◽  
Optimal Solution ◽  
Bat Algorithm ◽  
Cuckoo Search ◽  
Bee Colony ◽  
Bee Colony Optimization ◽  
Economic Dispatch Problem

This article is focused on hybrid method for solving the non-smooth cost function economic dispatch problem. The techniques were divided into two parts according to: the incremental cost rates are used to find the initial solution and bee colony optimization is used to find the optimal solution. The constraints of economic dispatch are power losses, load demand and practical operation constraints of generators. To verify the performance of the proposed algorithm, it is operated by the simulation on the MATLAB program and tests three case studies; three, six and thirteen generator units which compared to particle swarm optimization, cuckoo search algorithm, bat algorithm, firefly algorithm and bee colony optimization. The results show that the proposed algorithm is able to obtain higher quality solution efficiently than the others methods.

scholarly journals Cuckoo search algorithm for multi-objective supply chain problem

2018 ◽  
Vol 189 ◽  
pp. 06001 ◽  
Author(s):  
Fathy Elkazzaz ◽  
Abdelmageed Mahmoud ◽  
Ali Maher
Keyword(s):  
Supply Chain ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Chain Model ◽  
Multi Objective ◽  
Optimum Configuration ◽  
Bee Colony ◽  
Bee Colony Optimization ◽  
Chain Problem

A meta-heuristic algorithm called, the cuckoo search algorithm is proposed in dealing with the multi-objective supply chain model to find the optimum configuration of a given supply chain problem which minimizes the total cost and the total lead-time. The supply chain problem utilized in this study is taken from literature to show the performance of the proposed model; in addition, the results have been compared to those achieved by the bee colony optimization algorithm and genetic algorithm. Those obtained results indicate that the proposed cuckoo search algorithm is able to get better Pareto solutions (non-dominated set) for the supply chain problem.

scholarly journals Adaptation of optimization algorithm parameters to reconstruction of chaotic attractor

2015 ◽  
Vol 56 ◽  
Author(s):  
Miglė Drūlytė ◽  
Kristina Lukoševičiūtė ◽  
Erika Mekšunaitė
Keyword(s):  
Time Series ◽  
Time Delay ◽  
Optimization Algorithm ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Artificial Bee Colony Optimization ◽  
Bee Colony ◽  
Bee Colony Optimization ◽  
Selection Of

Optimal selection of time delay for time series reconstruction is an important problem in time series analysis and forecasting. When reconstructing the time series into phase space with non-uniform time delay, a time delay selection becomes a difficult optimization problem. To solve this problem, this paper presents two optimization algorithms: cuckoo search algorithm and artificial bee colony optimization algorithm.

scholarly journals Distributed Absorption and Half-Search Approach for Economic Dispatch Problem in Smart Grids

Energies ◽  
2019 ◽  
Vol 12 (8) ◽  
pp. 1527 ◽  
Author(s):  
Bo Li ◽  
Panpan Zhang ◽  
Xiangjun Li ◽  
Shengxian Cao
Keyword(s):  
Smart Grids ◽  
Search Algorithm ◽  
Economic Dispatch ◽  
Optimal Solution ◽  
Second Step ◽  
Distributed Approach ◽  
Economic Dispatch Problem ◽  
Search Approach ◽  
Consensus Information ◽  
Significant Class

The economic dispatch problem (EDP) is a significant class of optimization issues in the power system, which works on minimizing the total cost when generating a certain amount of power. A novel distributed approach for EDP is proposed in this paper. The presented approach consists of two steps. The first step, named absorption search, is to simplify the network structure through absorption searching. A flooding-based consensus approach is applied in the first step, which can be used to achieve consensus information among nodes. After the first step, only the generation nodes are kept in the network. The data collection can be completed by local computation and communication between neighbors. The first step can be considered as the stage of gathering information. In the second step, a distributed half-search algorithm makes the nodes obtain the final optimal solution in a distributed way. The results on three case studies demonstrate that the proposed approach is highly effective for solving the EDP.

scholarly journals Bee colony optimization with Taguchi method for solving the dynamic economic dispatch

2018 ◽  
Vol 185 ◽  
pp. 00033 ◽  
Author(s):  
Chia-Sheng Tu ◽  
Hsi-Shan Huang ◽  
Ming-Tang Tsai ◽  
Fu-Sheng Cheng
Keyword(s):  
Taguchi Method ◽  
Cost Function ◽  
Random Search ◽  
Economic Dispatch ◽  
Cost Functions ◽  
Optimal Dispatch ◽  
Bee Colony ◽  
Bee Colony Optimization ◽  
The Cost ◽  
Dynamic Economic Dispatch

Dynamic economic dispatch is to minimize the cost of power production of all the participating generators over a time horizon of 24 hours in one day. The dynamic economic dispatch with non-smooth cost functions, for which is formulated the optimal dispatch model of generations by considering the ramp up/down scheduling of power. This paper presents a Bee Colony Optimization (BCO) that applies the Taguchi Method (TM) to solve the Dynamic Economic Dispatch problem. The Taguchi method that involves the use of orthogonal arrays in estimating of the non-smooth cost function and Bee Colony Optimization is used to find the objective function under the operational of system constraints. The Taguchi method can global optimization for fast local convergence by minimizing the cost function in a few iterations. The effectiveness and efficiency of the TM-BCO is demonstrated by using a 10 unit of IEEE case with non-smooth fuel cost functions and is more effective than other previously developed algorithms. Moreover, the proposed approach presents significant computational benefits than traditional random search method especially for multi-unit systems with larger numbers of non-smooth cost functions and more complicated dynamic economic dispatch.

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