Abstract This paper proposes the Self-Adaptive algorithm for Multi-Objective Constrained Optimization by using Radial Basis Function Approximations, SAMO-COBRA. automatically determines best Function-fit as surrogates objectives well constraints, to find new feasible Pareto-optimal solutions. SAMO-COBRA is compared a wide set of other state-of-the-art algorithms (IC-SA-NSGA-II, SA-NSGA-II, NSGA...

 In this research, a tri-objective mathematical model is proposed for the Transportation-Location-Routing problem. The model considers a three-echelon supply chain and aims to minimize total costs, maximize the minimum reliability of the traveled routes and establish a well-balanced set of routes. In order to solve the proposed model, four metaheuristic algorithms, including Multi-Objective Gre...

Evolutionary algorithms have been recognized to be suitable for extracting approximate solutions of multi-objective problems because of their capability to evolve a set of non-dominated solutions distributed along the Pareto frontier‎. ‎This paper applies an evolutionary optimization scheme‎, ‎inspired by Multi-objective Invasive Weed Optimization (MOIWO) and Non-dominated Sorting (NS) strategi...

The process of service composition and optimal selection in cloud manufacturing (CMfg-SCOS) involves three types users: demanders, resource providers, platform operators. interests all users are a research focus CMfg-SCOS, as their participation the CMfg system directly affects efficiency long-term development CMfg. However, current on CMfg-SCOS rarely considers simultaneously, interest provide...

<span>Multi-objective algorithms are used to achieve high performance for quality of service (QoS) in wireless sensor networks (WSNs) is an important field researchers because these improve two or more conflicting objectives and present the best trade-off between solve multi-objective problems (MOPs). Previous research proposed algorithm that relies on non-dominated sorting genetic 3 (NSG...

Resource-constraint multi-project scheduling is one of the most important topic in the field of project management. Most current works solve this problem based on an idea that multiple projects can be simply emerged into a super-project in a deterministic environment, regardless of the project priority and robustness of schedules. This paper discusses the RCMPSP with priority and formulates a d...

Task scheduling is a crucial issue in distributed (disbursed) heterogeneous processing environment and significantly influence the performance of the system. The task scheduling problem has been identified to be NP-complete in its universal frame. In this paper the task scheduling problem is investigated using multiple-objective particle (molecule) swarm optimization algorithm with crowded disp...

The performance of horizontal axis tidal current turbines (HATCT) strongly depends on their geometry. According to this fact, the optimum performance will be achieved by optimized geometry. In this research study, the multi objective optimization of the HATCT is carried out by using four different multi objective optimization algorithms and their performance is evaluated in combination with bla...