This paper focus on artificial intelligence approaches to NP-hard job shop scheduling (JSS)
problem. In the literature successful approaches of artificial intelligence techniques such as …

As an extension of the classical job shop scheduling problem, the flexible job shop
scheduling problem (FJSP) plays an important role in real production systems. In FJSP, an …

This paper is intended to give a review of metaheuristic and their application to
combinatorial optimization problems. This paper comprises a snapshot of the rapid evolution …

Scheduling is a decision making process that takes care of the allocation of resources to
tasks over time. The Job Shop scheduling problem is one of the most complex scheduling …

Research in artificial intelligence demonstrates the applicability and flexibility of the
reinforcement learning (RL) technique for the dynamic job shop scheduling problem (DJSP) …

Considered one of the most innovative research directions, computational intelligence (CI)
embraces techniques that use global search optimization, machine learning, approximate …

One of the most difficult combinatorial optimization problems in recent studies is job shop
scheduling. Job shop scheduling which also holds the key to the company's profitability is a …

Computation is concerned with the validation of algorithm, estimation of complexity and
optimization. This requires large dataset analysis for the purpose of finding the unknown …

Job sequencing is the arrangement of the task that is to be performed or processed in a
machine in that particular order. Job sequencing problem has become the major problem in …

The scheduling problem of flow shop involves the benefit of production enterprise. In order
to solve the existing problems in the flow shop scheduling problem, a modified job shop …