Mixed-integer programming model and hybrid immune clone select algorithm for multi-objective double floor corridor allocation problem with vertical conveyor

Abstract

• Establish the model of Multi-Objective Double-Floor Corridor Allocation Problem • Propose a multi-objective hybrid immune clone select algorithm. • Validated the accuracy of the model and algorithms. • Exploring algorithm parameters and optimising a 24-scale production instance • The superiority of the proposed method is verified by comparing the solutions Detailed research on the impact of longitudinal material transportation mode and facility direction on the layout based on the double-floor corridor allocation problem (DFCAP) is lacking. Hence, we proposed a mixed-integer nonlinear programming (MINLP) model of a multi-objective DFCAP (MODFCAP) for minimising the material handling cost (MHC), minimising total layout area, and optimising the equilibrium index of double elevators. Moreover, we proposed a multi-objective clonal selection algorithm with variable neighbourhood search (VNS) operations (ICSAVNS) for solving MODFCAP efficiently. ICSAVNS performs a deep search of the population using the Metropolis-based VNS operation and also performs a breadth search through the two-segment mutation simultaneously. The accuracy of the model and algorithm is validated experimentally using a 9-scale calculation instance. We designed the Taguchi experiment to explore reasonable algorithm parameters and analysed the advantages and disadvantages of the layout schemes under different target preferences based on the results of a set of 24-scale production examples. Finally, the simulation instances of MODFCAP and bi-objective CAP are tested and compared with a series of algorithms. The results show that ICSAVNS can achieve the solution performance of the current advanced multi-objective algorithm.