Best-matching with interdependent preferences-implications for capacitated cluster formation and evolution

摘要: Generalized best-matching refers to matching the elements of two or more sets, on a many-to-one many-to-many basis, with respect their mutual preferences and capacity requirements/limits. problem (BMP) has variety applications in areas such as team network design, scheduling, transportation, routing, production planning, facility location, allocation, logistics. The is indeed analogous capacitated clustering problem, where set individuals are partitioned into disjoint clusters certain capacities. This work defines, formulates, analyzes an important behavior associated generalized BMP: influence same each other's preferences, if matched element other set. Such referred interdependent (IP). A binary program developed formulate provide basis for analyzing impact IP decisions from perspectives: Optimal cluster formation (fixed sets) evolution (emergent sets). evolutionary algorithms then handle complexity enable autonomously adapt random changes, recover, evolve. Results several experiments indicate (a) significant optimality decisions, (b) efficiency handling problem's complexity, emergent matching. notion introduced best problem.The (BMP-IP) problem.A novel quadratic programming formulation BMP-IP.Efficient heuristics clusters.Results show impacts static dynamic BMP.