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For multi-objective optimization problems (MOPs), the diversity of obtained solutions is of great importance for multi-objective evolutionary algorithms (MOEAs). To this end, in this paper, a new MOEA based on decomposition of a MOP into a number of constrained single-objective sub-problems (MOEA/D-MCS) is proposed. A MOP is firstly decomposed into a set of simple single-objective optimization sub-problems,...
This paper addresses the multiobjective permutation flow shop scheduling problem, where makespan and total flow time are to be minimized simultaneously. We solve the problem by an extended version of the multiobjective evolutionary algorithm based on decomposition (MOEA/D). We investigate the effects of scalarization functions and the replacement mechanism. We also incorporate local search into MOEA/D...
In addition to the need for satisfying several objectives, many problems in the real-world are also time-varying. These dynamic problems need the optimization algorithm to constantly find the time-varying optimal solutions. This paper proposes a dynamic multi-objective evolutionary algorithm based on decomposition and adaptive diversity introduction (denoted by dMOEAD-DI). Specifically, the dMOEAD-DI...
Synthesis gas production is widely used in chemical industries. Carbon dioxide reforming, steam reforming and partial-oxidation of methane are the main synthesis gas production methods. In this work, three objectives of maximize the selectivity of carbon monoxide, maximize the conversion of methane and minimize the hydrogen to carbon monoxide mole ratio which contain the variables of temperature,...
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