| Summary: | The real-life assembly production often has transportation between fabrication and assembly, and the capacity of transportation machine is often considered; however, the previous works are mainly about two-stage distributed assembly scheduling problems. In this study, a distributed energy-efficient assembly scheduling problem (DEASP) with transportation capacity is investigated, in which dedicated parallel machines with symmetry under the given conditions, transportation machines and an assembly machine are used. An adaptive imperialist competitive algorithm (AICA) is proposed to minimize makespan and total energy consumption. A heuristic and an energy-saving rule are used to produce initial solutions. An adaptive assimilation with adaptive global search and an adaptive revolution are implemented, in which neighborhood structures are chosen dynamically, and revolution probability and search times are decided by using the solution quality. The features of the problem are also used effectively. Computational experiments are conducted on a number of instances. The computational results demonstrate that the new strategies of AICA are effective and efficient and AICA can provide promising results for the considered DEASP.
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