We present a new non-dominated sorting algorithm to generate the non-dominated fronts in multi-objective optimization with evolutionary algorithms, particularly the NSGA-II. The non-dominated sorting algorithm used by NSGA-II has a time complexity of O(MN(2)) in generating non-dominated fronts in one generation (iteration) for a population size N and M objective functions. Since generating non-...

When large sensor networks are applied to the task of target tracking, it is necessary to successively identify subsets of sensors that are most useful at each time instant. Such a task involves simultaneously maximizing target detection accuracy and minimizing querying cost, addressed in this paper by the application of multi-objective evolutionary algorithms (MOEAs). The objective of maximizi...

We consider an open shop scheduling problem with setup and processing times separately such that not only the setup times are dependent on the machines, but also they are dependent on the sequence of jobs that should be processed on a machine. A novel bi-objective mathematical programming is designed in order to minimize the total tardiness and the makespan. Among several mult...

beneficial management practices (bmps) are important measures for reducing agricultural non-point source (nps) pollution. however, selection of bmps for placement in a watershed requires optimizing available resources to maximize possible water quality benefits. due to its iterative nature, the optimization typically takes a long time to achieve the bmp trade-off results which is not desirable ...

Cooperative coevolutionary evolutionary algorithms differ from standard evolutionary algorithms’ architecture in that the population is split into subpopulations, each of them optimising only a sub-vector of the global solution vector. All subpopulations cooperate by broadcasting their local partial solutions such that each subpopulation can evaluate complete solutions. Cooperative coevolution ...

Aiming at the problem of multimodal transport path planning under uncertain environments, this paper establishes a multi-objective fuzzy nonlinear programming model considering mixed-time window constraints by taking cost, time, and carbon emission as optimization objectives. To solve model, is de-fuzzified expectation value method chance-constrained method. Combining game theory with weighted ...

The time-cost trade-off problem is a known bi-objective problem in the field of project management. Recently, a new parameter, the quality of the project has been added to previously considered time and cost parameters. The main specification of the time-cost trade-off problem is discretization of the decision space to limited and accountable decision variables. In this situation the efficiency...

The present research proposes and optimizes the performance of a novel solar-driven combined cooling, heating, and power (CCHP) Kalina system for two seasons—winter and summer—based on exergy, exergo-economic, and exergo-environmental concepts applying a Non-dominated Sort Genetic Algorithm-II (NSGA-II) technique. Three criteria, i.e. daily exergy efficiency, total product cost rate, and to...