The Job-shop Scheduling Problem (JSSP) is a classical combinatorial optimization problem with significant implications for modern high-mix, low-volume manufacturing. Given its NP-hard complexity, local search based on critical-path-oriented neighborhood structures—specifically N5 through N8—has become a cornerstone of state-of-the-art metaheuristics. However, while existing literature focuses on their integration into complex frameworks like Tabu Search, their performance as standalone, basic local search (LS) is not yet fully understood. This obscures whether their efficacy is intrinsic to the neighborhood structures or dependent on the metaheuristic framework. Moreover, as these neighborhoods are nested, the incremental contribution of each additional move operator to objective function improvement has not been rigorously quantified. This paper presents a systematic empirical evaluation of the neighborhoods to elucidate their standalone effectiveness. Through extensive computational experiments on 28 standard benchmark instances, we comprehensively evaluate the impact of typical improvement strategies and neighborhood evaluation orders on search performance. Our findings demonstrate that the N8-based LS consistently outperforms other structures in terms of makespan reduction. Furthermore, a contribution analysis substantiates the practical utility of the nested neighborhood design, establishing the N8 structure as a potent intensification tool for manufacturing scheduling.
