Additive manufacturing (AM) has undergone significant development over the past decades,
resulting in vast amounts of data that carry valuable information. Numerous research studies …

Intelligent scheduling covers various tools and techniques for successfully and efficiently
solving the scheduling problems. In this paper, we provide a survey of intelligent scheduling …

Flexible job shop scheduling problem (FJSP) has been extensively considered; however,
multiobjective FJSP with energy consumption threshold is seldom investigated, the goal of …

In recent years, both distributed scheduling problem and energy-efficient scheduling have
attracted much attention. As the integration of these two problems, the distributed energy …

In this paper, an effective teaching–learning-based optimization algorithm (TLBO) is
proposed to solve the flexible job-shop problem with fuzzy processing time (FJSPF). First, a …

Fog computing is an emerging research domain to provide computational services such as
data transmission, application processing and storage mechanism. Fog computing consists …

Simulation Optimization (SO) techniques refer to a set of methods that have been applied to
stochastic optimization problems, structured so that the optimizer (s) are integrated with …

Distributed assembly flow shop scheduling problem (DAFSP) has been considered;
however, DAFSP with factory eligibility, transportation capacity and setup time is seldom …

Numerous problems encountered in real life cannot be actually formulated as a single
objective problem; hence the requirement of Multi-Objective Optimization (MOO) had arisen …

This paper presents a flexible job shop scheduling problem with fuzzy processing time. An
efficient decomposition-integration genetic algorithm (DIGA) is developed for the problem to …