This paper proposes a modified non-dominated sorting genetic algorithm (NSGA-II) for a bi-objective location-allocation model. The purpose is to define the best places and capacity of the distribution centers as well as to allocate consumers, in such a way that uncertain consumers demands are satisfied. The objectives of the mixed-integer non-linear programming (MINLP) model are to (1) minimize...

In this paper, we apply an elitist multi-objective genetic algorithm for solving mechanical component design problems with multiple objectives. Although there exists a number of classical techniques, evolutionary algorithms (EAs) have an edge over the classical methods in that they can find multiple Pareto-optimal solutions in one single simulation run. The proposed algorithm (we call NSGA-II) ...

The Evolutionary Computation has grown much in last few years. Inspired by biological evolution, this field is used to solve NP-hard optimization problems to come up with best solution. TSP is most popular and complex problem used to evaluate different algorithms. In this paper, we have conducted a comparative analysis between NSGA-II, NSGA-III, SPEA-2, MOEA/D and VEGA to find out which algorit...

With the development of customization concept, small-batch and multi-variety production will become one major modes, especially for fast-moving consumer goods. However, this mode has two issues: high cost long manufacturing period. To address these issues, study proposes a multi-objective optimization model flexible flow-shop to optimize scheduling, which would maximize efficiency by minimizing...

The present work focuses on evolving the multiple light-in-weight topologies of compliant mechanism tracing user defined path. Therefore in this paper, the bi-objective set is formulated first on the optimization frame-work in which the helper objective of maximum diversity is introduced with the primary objective of minimum weight of elastic structures. Thereafter, the evolutionary algorithm (...

Multi-objective evolutionary algorithms which use non-dominated sorting and sharing have been mainly criticized for their (i) O(mN3) computational complexity (where m is the number of objectives and N is the population size), (ii) non-elitism approach, and (iii) the need for specifying a sharing parameter. In this paper, we suggest a non-dominated sorting based multi-objective evolutionary algo...

Flexible job-shop scheduling problem (FJSP) is an NP-hard puzzle which inherits the job-shop scheduling problem (JSP) characteristics. This paper presents a bee evolutionary guiding nondominated sorting genetic algorithm II (BEG-NSGA-II) for multiobjective FJSP (MO-FJSP) with the objectives to minimize the maximal completion time, the workload of the most loaded machine, and the total workload ...

Determining the contribution of an agent to a system-level objective function (credit assignment) is a key area of research in cooperative multiagent systems. Multi-objective optimization is a growing area of research, though mostly focused on single agent settings. Many real-world problems are multiagent and multi-objective, (e.g., air traffic management, scheduling observations across multipl...

We compare the efficiency of the NSGA-II algorithm for the brachytherapy dose optimization problem with and without supporting solutions. A local search method enhances the efficiency of the algorithm. In comparison to a fast simulated annealing algorithm the supported hybrid NSGA-II algorithm provides much faster many non-dominated solutions. An archiving of all non-dominated solutions is usef...

The design of an urban water distribution system (WDS) is a challenging problem involving multiple objectives. The goal of robust multi-objective optimization for WDS design is to find the set of solutions which embodies an acceptable trade-off between system cost and reliability, so that the ideal solution may be selected for a given budget. In addition to satisfying consumer needs, a system m...