Two-Stage Assembly Scheduling with Batch Setup Times, Time-Dependent Deterioration, and Preventive Maintenance Activities Using Meta-Heuristic Algorithms

Abstract EN

This article considers a two-stage assembly scheduling problem (TSASP) with batch setup times, time-dependent deterioration, and preventive maintenance activities (PMAs).

The objective of this problem is to simultaneously determine the optimal component-manufacturing sequence (CMS), product-assembly sequence (PAS), number of setups, and number and position of PMAs (PPMA).

First, to determine the optimal solution, a novel mixed integer linear programming model (MILP) for the proposed problem is derived.

Then, a standard genetic algorithm (SGA), hybrid genetic algorithm (HGA), standard harmony search (SHS), hybrid harmony search (HHS), and harmony-search-based evolutionary algorithm (HSEA) were proposed owing to the intractability of the optimal solution for large-scale problems.

SGA and SHS provide a chromosome to represent a complete solution including three decisions (CMS, PAS, and PPMA).

HGA, HHS, and HSEA provide a chromosome to represent a partial solution including PAS.

CMS and PPMA are found by an effective local search heuristic based on the partial solution.

A computational experiment is then conducted to evaluate the impacts of the factors on the performance of the proposed algorithms.