Effective heuristic for large-scale unrelated parallel machines scheduling problems
Omega (United Kingdom)
This paper is concerned with non-preemptive scheduling of large-scale unrelated parallel machines (UPM) with the objective of minimizing total weighted completion times (TWCT). We propose a sequential improvement local search algorithm using multiple-jump strategy embedded within Tabu search (TS) components for TWCT, and use a highly efficient data structure to provide a necessary and sufficient condition for local optimality of a solution. We will generate a set of large-scale test problems to evaluate the performance of proposed algorithm in term of scalability, solution quality and efficiency. The non-parametric tests of algorithm components will be used to validate the consistent performance across problem types and problem sizes in the proposed algorithm.
Wang, Haibo and Alidaee, Bahram, "Effective heuristic for large-scale unrelated parallel machines scheduling problems" (2019). Business Faculty Publications. 35.