An efficient implementation of a VNS heuristic for the weighted fair sequences problem

Abstract

In the weighted fair sequences problem (WFSP), one aims to schedule a set of tasks or activities sthat the maximum product between the largest temporal distance between two consecutive executions of a task and its priority is minimized. The WFSP covers a large number of applications in different areas, ranging from automobile production on a mixed‐model assembly line to the sequencing of interactive applications to be aired in a digital TV environment. This paper proposes an iterative heuristic method for the WFSP centered on an efficient implementation of a variable neighborhood search heuristic. Computational experiments on benchmark instances show that the proposed metaheuristic outperforms the state‐of‐the‐art method proposed to the problem, obtaining comparable solution values in much less computational time.

An iterated greedy algorithm with variable reconstruction size for the obnoxious p‐median problem

“…This paper proposed a new algorithm for the OpM problem. It hybridises techniques from the IG and VNS metaheuristics, which are among the effective metaheuristics for optimisation problems (Demir, 2024;Rocha et al, 2024). It generalises previous ideas in the literature such as the reduced local search (Herrán et al, 2020) and the replacement of the facility swap operation with two consecutive operations of closing and opening a facility (Lin and Guan, 2018;Herrán et al, 2020).…”