A novel multi-objective metaheuristic algorithm for protein-peptide docking and benchmarking on the LEADS-PEP dataset

Author(s):  
Yosef Masoudi-Sobhanzadeh ◽  
Behzad Jafari ◽  
Sepideh Parvizpour ◽  
Mohammad M. Pourseif ◽  
Yadollah Omidi

We are interested by the problem of combinatorial auctions in which multiple items are sold and bidders submit bids on packages. First, we present a multi-objective formulation for a combinatorial auctions problem extending the existing single-objective models. Indeed, the bids may concern several specifications of the item, involving not only its price, but also its quality, delivery conditions, delivery deadlines, the risk of not being paid after a bid has been accepted and so on. The seller expresses his preferences upon the suggested items and the buyers are in competition with all the specified attributes done by the seller. Second, we develop and implement a metaheuristic algorithm based on a tabu search method.


2006 ◽  
Vol 169 (3) ◽  
pp. 898-917 ◽  
Author(s):  
B. de la Iglesia ◽  
G. Richards ◽  
M.S. Philpott ◽  
V.J. Rayward-Smith

Metals ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1311
Author(s):  
Seksan Winyangkul ◽  
Kittinan Wansaseub ◽  
Suwin Sleesongsom ◽  
Natee Panagant ◽  
Sumit Kumar ◽  
...  

This paper presents multi-objective topology and sizing optimization of a morphing wing structure. The purpose of this paper is to design a new aircraft wing structure with a tapered shape for ribs, spars, and skins including a torsion beam for external actuating torques, which is anticipated to modify the aeroelastic characteristic of the aircraft wing using multi-objective optimization. Two multi-objective topology optimization problems are proposed employing ground element structures with high- and low-grid resolutions. The design problem is to minimize mass, maximize difference of lift effectiveness, and maximize the buckling factor of an aircraft wing subject to aeroelastic and structural constraints including lift effectiveness, critical speed, and buckling factors. The design variables include aircraft wing structure dimensions and thickness distribution. The proposed optimization problems are solved by an efficient multi-objective metaheuristic algorithm while the results are compared and discussed. The Pareto optimal fronts obtained for all tests were compared based on a hypervolume metric. The objective function values for Case I and Case II at 10 selected optimal solutions exhibit a range of structural mass as 115.3216–411.6250 kg, 125.0137–440.5869 kg, lift effectiveness as 1.0514–1.1451, 1.0834–1.1639 and bucking factor as 38.895–1133.1864 Hz, 158.1264–1844.4355 Hz, respectively. The best results reveal unconventional aircraft wing structures that can be manufactured using additive manufacturing. This research is expected to serve as a foundation for future research into multi-objective topology optimization of morphing wing structures based on the ground element framework.


2021 ◽  
Author(s):  
Nima Khodadadi ◽  
Siamak Talatahari ◽  
Armin Dadras Eslamlou

Abstract In the present paper, a physics-inspired metaheuristic algorithm is presented to solve multi-objective optimization problems. The algorithm is developed based on the concept of Newtonian cooling law that recently has been employed by the Thermal Exchange Optimization (TEO) algorithm to efficiently solve single-objective optimization problems. The performance of the multi-objective version of TEO (MOTEO) is examined through bi- and tri-objective mathematical problems as well as bi-objective structural design examples. According to the comparisons between the MOTEO and several well-known algorithms, the proposed algorithm can provide quality Pareto fronts with appropriate accuracy, uniformity and coverage for multi-objective problems.


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