scholarly journals Optimizing the Joint Replenishment and Channel Coordination Problem under Supply Chain Environment Using a Simple and Effective Differential Evolution Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Lin Wang ◽  
Hui Qu ◽  
Shan Liu ◽  
Can Chen
Keyword(s):  
Supply Chain ◽  
Differential Evolution ◽  
Differential Evolution Algorithm ◽  
Cost Savings ◽  
Channel Coordination ◽  
Coordination Problem ◽  
Joint Replenishment ◽  
Np Hard Problem ◽  
Evolution Algorithm ◽  
Improved Differential Evolution Algorithm

This paper presents a useful and practical procurement approach using the joint replenishment and channel coordination (JR-CC) policy in a two-echelon supply chain considering the coordination cost. The objective is to determine a basic replenishment cycle time and the replenishment interval to minimize the total cost of the supply chain. To solve this NP-hard problem, a simple and improved differential evolution algorithm (IDE) is developed. The performance of the IDE is verified by benchmark functions. Moreover, results of comparative numerical example show the effectiveness of the proposed IDE. IDE can be used as a good candidate for the JR-CC model. Results of numerical examples also indicate that the JR-CC policy can result in considerable cost saving, and enhance the efficiency of a supply chain. But not all members in the supply chain can benefit a lot using this policy. Moreover, results of sensitivity analysis show that retailers have more willingness to adopt the JR-CC policy than the manufacturers because of the different cost savings.

scholarly journals An Effective Hybrid Self-Adapting Differential Evolution Algorithm for the Joint Replenishment and Location-Inventory Problem in a Three-Level Supply Chain

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Lin Wang ◽  
Hui Qu ◽  
Tao Chen ◽  
Fang-Ping Yan
Keyword(s):  
Supply Chain ◽  
Differential Evolution ◽  
Large Scale ◽  
Differential Evolution Algorithm ◽  
Complex Problem ◽  
Inventory Problem ◽  
Distribution Centers ◽  
Joint Replenishment ◽  
Evolution Algorithm ◽  
Comparative Results

The integration with different decisions in the supply chain is a trend, since it can avoid the suboptimal decisions. In this paper, we provide an effective intelligent algorithm for a modified joint replenishment and location-inventory problem (JR-LIP). The problem of the JR-LIP is to determine the reasonable number and location of distribution centers (DCs), the assignment policy of customers, and the replenishment policy of DCs such that the overall cost is minimized. However, due to the JR-LIP’s difficult mathematical properties, simple and effective solutions for this NP-hard problem have eluded researchers. To find an effective approach for the JR-LIP, a hybrid self-adapting differential evolution algorithm (HSDE) is designed. To verify the effectiveness of the HSDE, two intelligent algorithms that have been proven to be effective algorithms for the similar problems named genetic algorithm (GA) and hybrid DE (HDE) are chosen to compare with it. Comparative results of benchmark functions and randomly generated JR-LIPs show that HSDE outperforms GA and HDE. Moreover, a sensitive analysis of cost parameters reveals the useful managerial insight. All comparative results show that HSDE is more stable and robust in handling this complex problem especially for the large-scale problem.

The Economic Dispatch of Wind Integrated Power System based on an Improved Differential Evolution Algorithm

2020 ◽  
Vol 13 (3) ◽  
pp. 384-395
Author(s):  
Haiqing Liu ◽  
Jinmeng Qu ◽  
Yuancheng Li
Keyword(s):  
Differential Evolution ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Economic Dispatch ◽  
Differential Evolution Algorithm ◽  
Bee Colony ◽  
Evolution Algorithm ◽  
Improved Differential Evolution Algorithm ◽  
Dynamic Economic Dispatch ◽  
Integrated Power System

Background: As more and more renewable energy such as wind energy is connected to the power grid, the static economic dispatch in the past cannot meet its needs, so the dynamic economic dispatch of the power grid is imperative. Methods: Hence, in this paper, we proposed an Improved Differential Evolution algorithm (IDE) based on Differential Evolution algorithm (DE) and Artificial Bee Colony algorithm (ABC). Firstly, establish the dynamic economic dispatch model of wind integrated power system, in which we consider the power balance constraints as well as the generation limits of thermal units and wind farm. The minimum power generation costs are taken as the objectives of the model and the wind speed is considered to obey the Weibull distribution. After sampling from the probability distribution, the wind speed sample is converted into wind power. Secondly, we proposed the IDE algorithm which adds the local search and global search thoughts of ABC algorithm. The algorithm provides more local search opportunities for individuals with better evolution performance according to the thought of artificial bee colony algorithm to reduce the population size and improve the search performance. Results: Finally, simulations are performed by the IEEE-30 bus example containing 6 generations. By comparing the IDE with the other optimization model like ABC, DE, Particle Swarm Optimization (PSO), the experimental results show that obtained optimal objective function value and power loss are smaller than the other algorithms while the time-consuming difference is minor. The validity of the proposed method and model is also demonstrated. Conclusion: The validity of the proposed method and the proposed dispatch model is also demonstrated. The paper also provides a reference for economic dispatch integrated with wind power at the same time.

scholarly journals An Extended Flexible Job Shop Scheduling Model for Flight Deck Scheduling with Priority, Parallel Operations, and Sequence Flexibility

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Lianfei Yu ◽  
Cheng Zhu ◽  
Jianmai Shi ◽  
Weiming Zhang
Keyword(s):  
Differential Evolution ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Time Budget ◽  
Differential Evolution Algorithm ◽  
Mixed Integer ◽  
Aircraft Carrier ◽  
Evolution Algorithm ◽  
Improved Differential Evolution Algorithm ◽  
Flight Deck

Efficient scheduling for the supporting operations of aircrafts in flight deck is critical to the aircraft carrier, and even several seconds’ improvement may lead to totally converse outcome of a battle. In the paper, we ameliorate the supporting operations of carrier-based aircrafts and investigate three simultaneous operation relationships during the supporting process, including precedence constraints, parallel operations, and sequence flexibility. Furthermore, multifunctional aircrafts have to take off synergistically and participate in a combat cooperatively. However, their takeoff order must be restrictively prioritized during the scheduling period accorded by certain operational regulations. To efficiently prioritize the takeoff order while minimizing the total time budget on the whole takeoff duration, we propose a novel mixed integer liner programming formulation (MILP) for the flight deck scheduling problem. Motivated by the hardness of MILP, we design an improved differential evolution algorithm combined with typical local search strategies to improve computational efficiency. We numerically compare the performance of our algorithm with the classical genetic algorithm and normal differential evolution algorithm and the results show that our algorithm obtains better scheduling schemes that can meet both the operational relations and the takeoff priority requirements.

Sign in / Sign up

Export Citation Format

Share Document