The bi-objective double-floor corridor allocation problem (bDFCAP) investigated here explores the effective placement of given departments in a double-floor space to minimise the overall flow cost and the corridor length objectives. Within each floor, departments are arranged in two parallel rows on opposite sides along a central corridor without overlapping. In this study, the bDFCAP is formulated as a mixed integer linear programming model, which has improved the performance over the previous one. Thereafter, a genetic algorithm with a variable neighbourhood search technique is designed and employed to solve the bDFCAP in a more effective manner. This technique is utilized to improve the local search capability by adaptively transforming between a deep-searching strategy and broad-searching strategy, and the superior performance of the proposed method is proven through comparisons with two other algorithms in current literature. Besides, the state-of-the-art lower bounds of several benchmark instances are updated.

此处研究的双目标双层走廊分配问题（bDFCAP）探索了给定部门在双层空间中的有效放置，以最大程度地降低总体流动成本和走廊长度目标。在每层中，部门沿着中央走廊在相对的两侧以平行的两行布置，没有重叠。在这项研究中，bDFCAP被公式化为混合整数线性规划模型，与以前的模型相比，它已经提高了性能。此后，设计了一种具有可变邻域搜索技术的遗传算法，并将其用于更有效地求解bDFCAP。这项技术可通过在深度搜索策略和广泛搜索策略之间进行自适应转换来提高本地搜索功能，通过与现有文献中其他两种算法的比较证明了该方法的优越性能。此外，还更新了几个基准实例的最新下限。