This paper discusses the application of evolutionary multi-objective optimization algorithms namely Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and Modified NSGA-II (MNSGA-II) for solving the Combined Economic Emission Dispatch (CEED) problem with valvepoint loading. The valve-point loading introduce ripples in the input-output characteristics of generating units and make the CEED prob...

The decision-making of sustainable supply chain network (SSCN) design is a strategy capacity for configuring facility and product flow. When optimizing conflicting economic, environmental, social performance objectives, it difficult to select the optimal scheme from obtained feasible decision schemes. In this article, according triple bottom line sustainability, multi-objective optimization mod...

To solve single and multi-objective optimization problems, evolutionary algorithms have been created. We use the non-dominated sorting genetic algorithm (NSGA-II) to find Pareto front in a two-objective portfolio query, its extended variant NSGA-III three-objective problem, this article. Furthermore, both we quantify Karush-Kuhn-Tucker Proximity Measure (KKTPM) for each generation determine how...

A new hybrid multi-objective, multivariable optimizer utilizing Strength Pareto Evolutionary Algorithm (SPEA), Non-dominated Sorting Differential Evolution (NSDE), and Multi-Objective Particle Swarm (MOPSO) has been created and tested. The optimizer features automatic switching among these algorithms to expedite the convergence of the optimal Pareto front in the objective function(s) space. The...

A multi-objective particle swarm optimization (MOPSO) approach is presented for generating Pareto-optimal solutions for reservoir operation problems. This method is developed by integrating Pareto dominance principles into particle swarm optimization (PSO) algorithm. In addition, a variable size external repository and an efficient elitist-mutation (EM) operator are introduced. The proposed EM-...

Multi-energy systems (MES) allow various energy forms, such as electricity, gas, and heat, to interact achieve transfer mutually benefit, reducing the probability of load cutting in event a failure, increasing utilization efficiency, improving reliability robustness overall supply system. Since storage can help restore power case failure store surplus enhance flexibility MES, this work provides...

Cloud computing is an operation carried out via networks to provide resources and information end users according their demands. The job scheduling in cloud computing, which distributed across numerous for large-scale calculation resolves the value, accessibility, reliability, capability of important because high development technology many layers application. An extended revised study was deve...

AbstrAct: Muti-objective optimization deals with the simultaneous optimization of two or more conflicting objective functions in real-life systems. This paper deals with the multi-objective optimization in service systems. The goal of service systems is to provide cost-efficient service to customers, while at the same time, reducing the customer waiting time for service. In general, a low cost ...