Multi-Morphogen Fields and Homeostatic Resource Allocation for Constrained Multiobjective Evolutionary Optimization

Effective constrained multiobjective optimization requires a search process to coordinate feasibility attainment, objective-space progress, and population distribution under a limited evaluation budget. This coordination becomes more difficult in dual-population frameworks when auxiliary search loses objective-direction information, applies unsuitable constraint tolerance, or consumes resources that no longer match its current contribution. Motivated by these limitations, we develop the Multi-Morphogen Field-Guided Constrained Multiobjective Evolutionary Algorithm (MFGCMOEA). Its main population is responsible for feasibility-oriented convergence, whereas the auxiliary population encodes each objective through a separate morphogen channel. Signals are propagated according to relative geometry in objective-rank space, allowing local search information to modify the developmental state of each candidate. These channel-wise states are then used to construct individual constraint buffers and multidimensional phenotypes, so promising infeasible directions can remain competitive without collapsing multiple objectives into a single scalar evaluation. Diversity regulation is applied only when truncation is required on the critical developmental front. For computational coordination, MFGCMOEA derives resource evidence from offspring developmental quality and realized auxiliary recruitment and combines it with a symmetric basal-growth term to prevent overly polarized offspring allocation. The method was evaluated on 47 benchmark problems from four suites using 30 independent runs. Among nine algorithms, MFGCMOEA obtained the best overall mean ranks, approximately 1.66 for IGD and 1.74 for HV. On the 26 problems with complete valid results for all methods, the Friedman test detected significant overall differences, while Holm-adjusted pairwise comparisons favored MFGCMOEA against all eight competitors with large rank-biserial effect sizes. Additional convergence, distribution, ablation, and diagnostic results further confirm the roles of the developmental-field representation and homeostatic resource regulation.