Minimizing maximum tardiness subject to collect the EOL products in a single machine scheduling problem with capacitated batch delivery and pickup systems

• Published in: Computers & industrial engineering Vol. 161; p. 107634
• Main Author: Rostami, Mohammad
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.11.2021
• Subjects: Branch and bound algorithm; Case study; Closed-loop batch delivery system; Maximum tardiness; Mixed integer linear programming; Sustainability; Closed-loop batch delivery system; Maximum tardiness; Case study; Branch and bound algorithm; Mixed integer linear programming; Sustainability
• ISSN: 0360-8352; 1879-0550
• DOI: 10.1016/j.cie.2021.107634

•The capacitated closed-loop batch delivery system is introduced for the first time.•A comprehensive and integrated mixed integer linear programming model is developed.•Two innovative lower bounds are introduced.•A novel branch and bound algorithm is developed.•A case study based on motor oil supply chain is presented. This paper introduces capacitated batch delivery and pickup systems (here it is named closed-loop batch delivery systems) in an integrated production scheduling and distribution operation problem for the first time. A comprehensive and integrated model is developed for production scheduling, delivering products to the multiple customers using batch delivery system, and picking-up End of Life (EOL) products in order to recycle and reuse in the manufacturer plant. The aim of this model is to minimize the maximum tardiness subject to collect the EOL product in order to improve sustainability. First, a Mixed Integer Linear Programming (MILP) model is developed to solve small-size instances. Due to the fact that this problem is NP-hard, a branch and bound algorithm is developed by introducing effective lower bounds in order to obtain optimal solutions for the large-size instances. In order to show the application of the problem, a real case study in a motor oil supply chain is presented. The results illustrate that paying attention to the problem of collecting used motor oils through simultaneous pick-up and delivery can reduce their disposal in nature or reduce non-standard recycling of motor oil, which in turn improves sustainability. Finally, experimental results on the random generation problems show that the proposed branch and bound algorithm is especially useful to solve large-size instances.