A green-oriented bi-objective disassembly line balancing problem with stochastic task processing times

Abstract

Remanufacturing and recycling industry has developed rapidly in recent years due to its benefits in reducing waste and protecting the environment. However, the uncertain environment and excessive emission during production become two main obstacles for its further development. In this paper, a green-oriented bi-objective disassembly line balancing problem with stochastic task processing times is studied. The objectives are to minimize the total line configuration cost respecting the given budget, and minimize the total contaminant emission, respectively. To depict stochastic processing times, their mean, standard deviation and change-rate upper bound are assumed to be known since it may be difficult to obtain the complete historical data. For the problem, a bi-objective model with chance constraints is first formulated, which is further approximated into a linear distribution-free one. To solve the second model, an efficient $$\varepsilon $$ -constraint method is proposed based on problem analysis. Finally, a fuzzy-logic-based approach is applied to recommend preferred solutions for managers according to their perspectives. The solution methods are first examined by a case study, then by 247 benchmark-based instances and randomly generated instances. Experimental results indicate the efficiency and effectiveness of the proposed methods for solving the green-oriented bi-objective problem.