[1] The operation of large-scale water resources systems often involves several conflicting and noncommensurable objectives. The full characterization of tradeoffs among them is a necessary step to inform and support decisions in the absence of a unique optimal solution. In this context, the common approach is to consider many single objective problems, resulting from different combinations of ...

Abstract Multi-objective particle swarm optimization algorithms encounter significant challenges when tackling many-objective problems. This is mainly because of the imbalance between convergence and diversity that occurs increasing selection pressure. In this paper, a novel adaptive MOPSO (ANMPSO) algorithm based on R2 contribution method developed to improve performance MOPSO. First, new glob...

AMA Fram K, Saleh S, R, et al. The shift in COVID-19 vaccination policy for pregnant women, from restricted to required, and the confusion that ensued. Menopause Review/Przegląd Menopauzalny. 2023. doi:10.5114/pm.2023.127773. APA Fram, K., Saleh, S., R., Khalaf, T., Almasoud, & Almukaimi, B. (2023). https://doi.org/10.5114/pm.2023.127773 Chicago Kamil Mosa, Shawqi Rand Taiba Shrouq Bader Sondos...

Abstract There are many complex multi-objective optimization problems in the real world, which difficult to solve using traditional methods. Multi-objective particle swarm is one of effective algorithms such problems. This paper proposes a with dynamic population size (D-MOPSO), helps compensate for lack convergence and diversity brought by optimization, makes full use existing resources search...

The structural parameters of the magnetorheological (MR) damper significantly affect output damping force and dynamic range. This paper presents a design optimization method to improve performance novel MR with bended magnetic circuit folded flow gap. multiobjective this was carried out based on optimal Latin hypercube (Opt LHD), ellipsoidal basis function neural network (EBFNN), particle swarm...

The near net shaped manufacturing ability of squeeze casting process requiresto set the process variable combinations at their optimal levels to obtain both aesthetic appearance and internal soundness of the cast parts. The aesthetic and internal soundness of cast parts deal with surface roughness and tensile strength those can readily put the part in service without the requirement of costly s...

Pareto based Multi-Objective Evolutionary Algorithms face several problems when dealing with a large number of objectives. In this situation, almost all solutions become nondominated and there is no pressure towards the Pareto Front. The use of Particle Swarm Optimization algorithm (PSO) in multi-objective problems grew in recent years. The PSO has been found very efficient in solve Multi-Objec...

In this paper the multi-mode resource-constrained project scheduling problem with discounted cash flows is considered. Minimizing the makespan and maximization the net present value (NPV) are the two common objectives that have been investigated in the literature. We apply one evolutionary algorithm named multiobjective particle swarm optimization (MOPSO) to find Pareto front solutions. We used...

Proper and realistic scheduling is an important factor of success for every project. In reality, project scheduling often involves several objectives that must be realized simultaneously, and faces numerous uncertainties that may undermine the integrity of the devised schedule. Thus, the manner of dealing with such uncertainties is of particular importance for effective planning. A realistic sc...

Preventive healthcare aims at reducing the likelihood and severity of potentially life-threatening illnesses by protection and early detection. In this paper, a bi-objective mathematical model is proposed to design a network of preventive healthcare facilities so as to minimize total travel and waiting time as well as establishment and staffing cost. Moreover, each facility acts as M/M/1 queuin...