A large number of near-obsolete agricultural machinery can be produced with the agricultural intelligentization and the life cycle of machinery equipment in recent years. Among them, the disassembly and recycling of agricultural machinery and equipment can play an important role in the utilization of ecological resources and sustainable agriculture. The recycling of obsolete agricultural machinery products can also greatly contribute to realizing sustainable development and a circular economy under the carbon peak and carbon neutrality. This study aims to perform the integration optimization of obsolete agricultural machinery product disassembly planning and remanufacturing decisions under the requirements of dual carbon target. The economic benefits were also evaluated to consider the carbon emission cost of the disassembly process. Firstly, a disassembly and remanufacturing integrated optimization model (DRIO) was constructed using product depreciation rate, remanufacturing demand and cost. The mathematical model included the profit maximization of remanufacturing product revenue, such as the cost of acquisition, disassembly, remanufacturing, and carbon emission. Secondly, an improved artificial bee colony algorithm (IABC) was proposed to solve the mathematical model. A set of Pareto schemes were obtained with high profit and low environmental carbon emission. The improved ABC algorithm included the population initialization, bee hiring, watch, and bee scout stage. A logistic mapping was introduced to generate high-quality initial solutions. A neighborhood search mechanism was added to the hire and watch bee phases, in order to enhance the colony search with less local optimality. A roulette wheel was also used in the scout bee phase. The motor was one of the main recycling and remanufacturing components of agricultural machinery, indicating the strong universality and high recycling-remanufacturing profit. Finally, the effectiveness and feasibility of the system were verified by an example of combined harvester disassembly. A collection was generated for the reuse, recycling, and remanufacturing of parts of the motor EOL decision. The results show that the economic benefits of the improved DRIO model were improved by 62.1% and 54.8%, respectively, compared with the DRIO-D and DRIO-R models. The carbon cost of the DRIO and DRIO-R models was about 50% less than that of the DRIO-D model. The characteristic index was chosen to measure the convergence of the super volume reaction non-inferior solution, and the dispersion degree of the reaction solution was measured by the spacing. The solution time of IABC was shortened by 19.3%, and the number of feasible solutions increased by 28.6%, compared with the classical. The improved DRIO model presented better economic benefits than DRIO-D and DRIO-R models. The IABC shared better performance, in terms of robustness and convergence. The solution time of IABC was shortened by 47.8%, and the number of feasible solutions was doubled than before. In the super volume value, the artificial bee colony algorithm (2.695) was similar to the ant colony algorithm (2.377), but both were smaller than the IABC algorithm (2.813). In the spacing measure, the ant colony algorithm (0.052 3) was lower than the artificial colony algorithm (0.068 2), but the IABC (0.041 6) was the lowest. Therefore, the integrated optimization model of disassembly planning constructed can be effectively improved the economic benefits of the disassembly and recycling of waste agricultural machinery recycling products, for less carbon emissions. The finding can provide an important basis for the formulation of relevant standards, together with the decision support for the green design of agricultural machinery.