An effective neighborhood search for scheduling in dual-resource constrained interval job shop with environmental objective

In this study, scheduling problem in dual-resource constrained (DRC) job shop with interval processing time and heterogeneous resources is investigated. A lexicographical method is applied to minimize interval carbon footprint and makespan. A dynamical neighborhood search (DNS) is proposed, which is composed of two phases. Two-string representation is used and its chromosome consists of the operation-based string and the resource string. Several initial solutions are produced and improved in the first phase and only one solution is applied in the second phase. Four neighborhood structures and their dynamical transition mechanism are utilized to produce new solutions. DNS is tested on a number of instances and compared with other algorithms. Computational experiments show DNS can provide the promising results for the problem.