| Modern information warfare is unexpected and with fast rhythm, hence the speed and effectiveness of the war mobilization organizations become a key factor in the war process and result. During the Military exercises or real war, as veterans retired, fighting injuries, illness, new recruits and other reasons, large numbers of combat troops will fill the new recruits, Battle groups having been formed need to restructure. The organizational structure can be optimized to increase the battle effectiveness respect to the relative stable military personnel and weaponry.Battle Group In Forces issues involving personnel attributes and many more factors affecting the groups, it is dynamic planning, The Group is a tremendous amount, traditional methods is hard to accurately assess the contribution of various factors to the battle effectiveness. To address this problem, this thesis makes following contributions:1) Analysis of the battle effectiveness forming system and its impact factors, formalized describes a mathematical model of Battle Group In Forces.2) Proposes three fuzz quantified models of combatants attributes, and an Flexibility Synthetical Efficiency Algorithm (FSEA).3) Proposes algorithm GepBE (GEP-Battle Effectiveness) for function finding. The algorithm can mine battle effectiveness relations function of Specialized forces fighting units,To assess the effectiveness of the fighting, and Battle Group In Forces provide scientific measurement function.4) Proposes the model named Caching GepFG (GEP-flak-Group) model based on the Gene Expression Programming to solve the problem of Battle Group In Forces. |
