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 A Multi-Objective Optimization for Supply Chain Network Using the Bees Algorithm

10.5772/56754 ◽  
2013 ◽  
Vol 5 ◽  
pp. 38 ◽  
Author(s):  
Ernesto Mastrocinque ◽  
Baris Yuce ◽  
Alfredo Lambiase ◽  
Michael S. Packianather
Keyword(s):  
Supply Chain ◽  
Lead Time ◽  
Cost Minimization ◽  
Optimization Method ◽  
Bees Algorithm ◽  
Chain Model ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Optimum Configuration ◽  
Chain Problem

A supply chain is a complex network which involves the products, services and information flows between suppliers and customers. A typical supply chain is composed of different levels, hence, there is a need to optimize the supply chain by finding the optimum configuration of the network in order to get a good compromise between the multi-objectives such as cost minimization and lead-time minimization. There are several multi-objective optimization methods which have been applied to find the optimum solutions set based on the Pareto front line. In this study, a swarm-based optimization method, namely, the bees 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 and several experiments have been conducted in order to show the performance of the proposed model; in addition, the results have been compared to those achieved by the ant colony optimization method. The results show that the proposed bees algorithm is able to achieve better Pareto solutions for the supply chain problem.

scholarly journals Optimization strategy of wireless charger node deployment based on improved cuckoo search algorithm

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yang Wang ◽  
Feifan Wang ◽  
Yujun Zhu ◽  
Yiyang Liu ◽  
Chuanxin Zhao
Keyword(s):  
Sensor Network ◽  
Sensor Node ◽  
Search Algorithm ◽  
Optimal Solution ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Sensor Nodes ◽  
Optimization Strategy ◽  
Multi Objective ◽  
Received Power

AbstractIn wireless rechargeable sensor network, the deployment of charger node directly affects the overall charging utility of sensor network. Aiming at this problem, this paper abstracts the charger deployment problem as a multi-objective optimization problem that maximizes the received power of sensor nodes and minimizes the number of charger nodes. First, a network model that maximizes the sensor node received power and minimizes the number of charger nodes is constructed. Second, an improved cuckoo search (ICS) algorithm is proposed. This algorithm is based on the traditional cuckoo search algorithm (CS) to redefine its step factor, and then use the mutation factor to change the nesting position of the host bird to update the bird’s nest position, and then use ICS to find the ones that maximize the received power of the sensor node and minimize the number of charger nodes optimal solution. Compared with the traditional cuckoo search algorithm and multi-objective particle swarm optimization algorithm, the simulation results show that the algorithm can effectively increase the receiving power of sensor nodes, reduce the number of charger nodes and find the optimal solution to meet the conditions, so as to maximize the network charging utility.

Solving multi-objective optimization problem using cuckoo search algorithm based on decomposition

2020 ◽  
Vol 51 (1) ◽  
pp. 143-160
Author(s):  
Liang Chen ◽  
Wenyan Gan ◽  
Hongwei Li ◽  
Kai Cheng ◽  
Darong Pan ◽  
...  
Keyword(s):  
Optimization Problem ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Multi Objective Optimization ◽  
Multi Objective
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