Neighbourhood search-based metaheuristics for the bi-objective Pareto optimization of total weighted earliness-tardiness and makespan in a JIT single machine scheduling problem
Year: 2025
Type: article
Abstract: This paper studies the simultaneous minimization of total weighted earliness-tardiness (TWET) and makespan in a just-in-time single-machine scheduling problem (JIT-SMSP). The problem considers sequence-dependent setup times (SDST) between the jobs, distinct due windows for each job, and allows idle times to be inserted in the schedules. Since the problem belongs to the NP-hard category, multiple variants of neighbourhood search-based metaheuristic algorithms, viz. iterated local search (ILS), variable neighbourhood search (VNS) and variable neighbourhood descent (VND), are proposed to generate Pareto-optimal solutions to the problem. The proposed algorithms employ five different neighbourhood generation mechanisms to perturb and improve the sequences of jobs to generate the Pareto-optimal front. Since idle times are allowed to be inserted in the schedules, each sequence of jobs results in a piecewise linear convex trade-off curve between the TWET and makespan objectives. An optimal timing algorithm (OTA) is presented to generate the trade-off curve between the two objectives for a given sequence of jobs. The trade-off curves generated corresponding to the sequences of jobs by the proposed metaheuristics are trimmed and merged using a Pareto front generation procedure to generate the Pareto-optimal front comprising line segments and points. The computational performance of the proposed algorithms is evaluated with test instances of varying sizes using four performance metrics devised to compare Pareto fronts comprising line segments and points. The performance comparisons reveal that the variants of VND outperform the other algorithms in most performance metrics.
Source: Operations Research Perspectives
Authors: Sona Babu, B.S. Girish
Institution: Indian Institute of Space Science and Technology
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,790
OpenAlex ID: W4408734167