scholarly journals A new hybrid approach based on discrete differential evolution algorithm to enhancement solutions of quadratic assignment problem

2020 ◽  
pp. 51-72 ◽  
Author(s):  
Asaad Shakir Hameed ◽  
Burhanuddin Mohd Aboobaider ◽  
Modhi Lafta Mutar ◽  
Ngo Hea Choon
Keyword(s):  
Differential Evolution ◽  
Assignment Problem ◽  
Quadratic Assignment Problem ◽  
Hybrid Approach ◽  
Differential Evolution Algorithm ◽  
Quadratic Assignment ◽  
Evolution Algorithm ◽  
Discrete Differential Evolution

Discrete Differential Evolution Algorithm for Solving the Terminal Assignment Problem

2010 ◽  
pp. 229-239 ◽  
Author(s):  
Eugénia Moreira Bernardino ◽  
Anabela Moreira Bernardino ◽  
Juan Manuel Sánchez-Pérez ◽  
Juan Antonio Gómez-Pulido ◽  
Miguel Angel Vega-Rodríguez
Keyword(s):  
Differential Evolution ◽  
Assignment Problem ◽  
Differential Evolution Algorithm ◽  
Evolution Algorithm ◽  
Discrete Differential Evolution

scholarly journals A Hybrid Method Integrating a Discrete Differential Evolution Algorithm with Tabu Search Algorithm for the Quadratic Assignment Problem: A New Approach for Locating Hospital Departments

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Asaad Shakir Hameed ◽  
Modhi Lafta Mutar ◽  
Haiffa Muhsan B. Alrikabi ◽  
Zakir Hussain Ahmed ◽  
Abeer A. Abdul–Razaq ◽  
...  
Keyword(s):  
Tabu Search ◽  
Differential Evolution ◽  
Hybrid Method ◽  
Assignment Problem ◽  
Quadratic Assignment Problem ◽  
Quadratic Assignment ◽  
Layout Problem ◽  
Facility Layout Problem ◽  
Benchmark Instances ◽  
Discrete Differential Evolution

The facility layout problem (FLP) is a very important class of NP-hard problems in operations research that deals with the optimal assignment of facilities to minimize transportation costs. The quadratic assignment problem (QAP) can model the FLP effectively. One of the FLPs is the hospital facility layout problem that aims to place comprehensive clinics, laboratories, and radiology units within predefined boundaries in a way that minimizes the cost of movement of patients and healthcare personnel. We are going to develop a hybrid method based on discrete differential evolution (DDE) algorithm for solving the QAP. In the existing DDE algorithms, certain issues such as premature convergence, stagnation, and exploitation mechanism have not been properly addressed. In this study, we first aim to discover the issues that make the current problem worse and to identify the best solution to the problem, and then we propose to develop a hybrid algorithm (HDDETS) by combining the DDE and tabu search (TS) algorithms to enhance the exploitation mechanism in the DDE algorithm. Then, the performance of the proposed HDDETS algorithm is evaluated by implementing on the benchmark instances from the QAPLIB website and by comparing with DDE and TS algorithms on the benchmark instances. It is found that the HDDETS algorithm has better performance than both the DDE and TS algorithms where the HDDETS has obtained 42 optimal and best-known solutions from 56 instances, while the DDE and TS algorithms have obtained 15 and 18 optimal and best-known solutions out of 56 instances, respectively. Finally, we propose to apply the proposed algorithm to find the optimal distributions of the advisory clinics inside the Azadi Hospital in Iraq that minimizes the total travel distance for patients when they move among these clinics. Our application shows that the proposed algorithm could find the best distribution of the hospital’s rooms, which are modeled as a QAP, with reduced total distance traveled by the patients.

scholarly journals WSNs Compressed Sensing Signal Reconstruction Based on Improved Kernel Fuzzy Clustering and Discrete Differential Evolution Algorithm

2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
Zhou-zhou Liu ◽  
Shi-ning Li
Keyword(s):  
Compressed Sensing ◽  
Differential Evolution ◽  
Fuzzy Clustering ◽  
Clustering Algorithm ◽  
Signal Reconstruction ◽  
Differential Evolution Algorithm ◽  
Reconstruction Algorithm ◽  
Reconstruction Algorithms ◽  
Evolution Algorithm ◽  
Discrete Differential Evolution

To reconstruct compressed sensing (CS) signal fast and accurately, this paper proposes an improved discrete differential evolution (IDDE) algorithm based on fuzzy clustering for CS reconstruction. Aiming to overcome the shortcomings of traditional CS reconstruction algorithm, such as heavy dependence on sparsity and low precision of reconstruction, a discrete differential evolution (DDE) algorithm based on improved kernel fuzzy clustering is designed. In this algorithm, fuzzy clustering algorithm is used to analyze the evolutionary population, which improves the pertinence and scientificity of population learning evolution while realizing effective clustering. The differential evolutionary particle coding method and evolutionary mechanism are redefined. And the improved fuzzy clustering discrete differential evolution algorithm is applied to CS reconstruction algorithm, in which signal with unknown sparsity is considered as particle coding. Then the wireless sensor networks (WSNs) sparse signal is accurately reconstructed through the iterative evolution of population. Finally, simulations are carried out in the WSNs data acquisition environment. Results show that compared with traditional reconstruction algorithms such as StOMP, the reconstruction accuracy of the algorithm proposed in this paper is improved by 36.4-51.9%, and the reconstruction time is reduced by 15.1-31.3%.

Research on Optimization Technology of Facility Layout Based on Improved Differential Evolution Method

2014 ◽  
Vol 912-914 ◽  
pp. 1706-1709
Author(s):  
Ping Bo Qu
Keyword(s):  
Differential Evolution ◽  
Quadratic Assignment Problem ◽  
Facility Layout ◽  
Differential Evolution Algorithm ◽  
Layout Design ◽  
Quadratic Assignment ◽  
Problem Model ◽  
Facility Layout Design ◽  
Facility Logistics ◽  
The Cost

The facility layout design is the key problem in manufacturing system. Based on the constraints such as the cost of facility logistics and the space of equipment, this paper sets up a Quadratic Assignment Problem model of facility layout. The model is solved using Differential Evolution algorithm according to the features of facility layout, which is combined with Random Key technology. The test results performed on the liner and circular layout show the proposed approach can solve effectively the facility layout design problem.

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