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Recent advances in on-board radar and missile capabilities, combined with individual payload limitations, have led to increased interest in the use of unmanned combat aerial vehicles (UCAVs) for cooperative occupation during beyond-visual-range (BVR) air combat. However, prior research on occupational decision-making in BVR air combat has mostly been limited to one-on-one scenarios. As such, this study presents a practical cooperative occupation decision-making methodology for use with multiple UCAVs. The weapon engagement zone (WEZ) and combat geometry were first used to develop an advantage function for situational assessment of one-on-one engagement. An encircling advantage function was then designed to represent the cooperation of UCAVs, thereby establishing a cooperative occupation model. The corresponding objective function was derived from the one-on-one engagement advantage function and the encircling advantage function. The resulting model exhibited similarities to a mixed-integer nonlinear programming (MINLP) problem. As such, an improved discrete particle swarm optimization (DPSO) algorithm was used to identify a solution. The occupation process was then converted into a formation switching task as part of the cooperative occupation model. A series of simulations were conducted to verify occupational solutions in varying situations, including two-on-two engagement. Simulated results showed these solutions varied with initial conditions and weighting coefficients. This occupation process, based on formation switching, effectively demonstrates the viability of the proposed technique. These cooperative occupation results could provide a theoretical framework for subsequent research in cooperative BVR air combat.