Multi-Objective Optimization (MOO) techniques often achieve the combination of both maximization and minimization objectives. The study suggests scalarizing the multi-objective functions simpler using duality. An exam...Multi-Objective Optimization (MOO) techniques often achieve the combination of both maximization and minimization objectives. The study suggests scalarizing the multi-objective functions simpler using duality. An example of four objective functions has been solved using duality with satisfactory results.展开更多
The paper evaluates the suitability of examples used in developing averaging techniques of multi-objective optimization (MOO). Most of the examples used for proposing these techniques were not suitable. The results of...The paper evaluates the suitability of examples used in developing averaging techniques of multi-objective optimization (MOO). Most of the examples used for proposing these techniques were not suitable. The results of these examples have also not been interpreted correctly. An appropriate example has also been solved with existing and improved averaging techniques of multi-objective optimization.展开更多
Multi</span><span><span style="font-family:"">-</span></span><span><span style="font-family:"">goal and multi-objective optimizations are similar...Multi</span><span><span style="font-family:"">-</span></span><span><span style="font-family:"">goal and multi-objective optimizations are similar techniques to</span></span><span><span style="font-family:""> achieve <span>multiple conflicting goals/objectives simultaneously. There are several tech</span>niques <span>for solving multi-goal and multi-objective optimization problems. The</span> <span>present </span><span>study proposed the possibility of convertibility in solving multi-goal and mul</span>ti-objective optimization problems.展开更多
文摘Multi-Objective Optimization (MOO) techniques often achieve the combination of both maximization and minimization objectives. The study suggests scalarizing the multi-objective functions simpler using duality. An example of four objective functions has been solved using duality with satisfactory results.
文摘The paper evaluates the suitability of examples used in developing averaging techniques of multi-objective optimization (MOO). Most of the examples used for proposing these techniques were not suitable. The results of these examples have also not been interpreted correctly. An appropriate example has also been solved with existing and improved averaging techniques of multi-objective optimization.
文摘Multi</span><span><span style="font-family:"">-</span></span><span><span style="font-family:"">goal and multi-objective optimizations are similar techniques to</span></span><span><span style="font-family:""> achieve <span>multiple conflicting goals/objectives simultaneously. There are several tech</span>niques <span>for solving multi-goal and multi-objective optimization problems. The</span> <span>present </span><span>study proposed the possibility of convertibility in solving multi-goal and mul</span>ti-objective optimization problems.
