Sequential Memetic Algorithm Optimization for Allocation Planning in Hostelry Establishments

Abstract

Hostelry establishments face the challenge of devising a table and chair allocation for accommodating their customers on a daily basis. This problem scales significantly with the introduction of constraints, such as scenario obstacles or the requirement of a minimum distance separation. The TLP (Table Location Problem) and the CLP (Chair Location Problem) are NP-Hard complexity problems that aim to attain the optimal table and chair distribution for certain applications. Existing approaches to this problem fail to address both the TLP and CLP simultaneously, thus resulting in suboptimal solutions achieved by imposing optimization constraints. Therefore, in this paper, a sequential optimization methodology based on a GBLS MA (Gradient-Based Local Search Memetic Algorithm) optimizations is proposed for optimizing the table and chair disposition simultaneously while also considering scenario and distancing restrictions. The proposed methodology is then implemented into a realistic establishment, where different optimization strategies within the CLP are compared. Results prove the viability and flexibility of the proposed sequential optimization for complex hostelry scenarios.

Keywords

• table location problem
• chair location problem
• maximum diversity problem
• memetic algorithm
• NP-Hard