Due to the stubborn nature of the deterministic job-shop scheduling problem many solutions
proposed are of hybrid construction cutting across the traditional disciplines. The problem …

Job-shop scheduling problem (abbreviated to JSP) is one of the well-known hardest
combinatorial optimization problems. During the last three decades, the problem has …

Delivering services for Internet of Things (IoT) applications that demand real-time and
predictable latency is a challenge. Several IoT applications require stringent latency …

Research on scheduling problems is an evergreen challenge for industrial engineers. The
growth of digital technologies opens the possibility to collect and analyze great amount of …

In recent years, there has been a growing concern over the environmental impact of
traditional manufacturing, especially in terms of energy consumption and related emissions …

Michael L. Pinedo Theory, Algorithms, and Systems Sixth Edition Page 1 Scheduling Michael L.
Pinedo Theory, Algorithms, and Systems Sixth Edition Page 2 Scheduling Page 3 Michael L …

A comprehensive guide to a powerful new analytical tool by two of its foremost innovators
The past decade has witnessed many exciting advances in the use of genetic algorithms …

In both industry and the research literature, Mixed Integer Programming (MIP) is often the
default approach for solving scheduling problems. In this paper we present and evaluate …

Random-key genetic algorithms were introduced by Bean (ORSA J. Comput. 6: 154–160,
1994) for solving sequencing problems in combinatorial optimization. Since then, they have …

Metaheuristics are the most exciting development in approximate optimization techniques of
the last two decades. They have had widespread successes in attacking a variety of difficult …