The present paper extends the idea of job shop scheduling problem with resting constraints to the train scheduling problem with the Muslim praying considerations. For this purpose, after proposing the new mathematical model, a heuristic algorithm based on the Electromagnetism-Like algorithm (EM) which is well adjusted to scheduling problems is employed to solve the large-size practical cases. T...

Traditional scheduling problems with the batch processing machines (BPM) assume that machines are continuously available, and no time is needed for their preventive maintenance (PM). In this paper, we study a realistic variant of flowshop scheduling which integrates flow shop batch processing machines (FBPM) and preventive maintenance for minimizing the makespan. In order to tackle the given pr...

This paper presents an efficient meta-heuristic algorithm based on electromagnetism-like method, which has been successfully implemented in multiuser detection problems. The contribution revisits blind multiuser detection for multicarrier code division multiple access systems using a novel combined adaptive step-size constant modulus algorithm (CMA) and electromagnetism-like method scheme. To w...

In this paper, we present on a periodic job shop scheduling problem (PJSSP) based on the periodic event scheduling problem (PESP), which is different from cyclic scheduling. The PESP schedules a number of recurring events, such that each pair of events fulfills certain constraints during a given time period. To solve such a hard PJSS problem, we propose a hybrid algorithm, namely EM–SA, which i...

Due to random deployment of static sensor nodes and environmental factors existence of holes in wireless sensor networks is inevitable. This holes results in reducing the data transmission performance and in additional energy consumption. Consequently, the hole problem is an important factor for prolonging the network lifetime. The network lifetime can be improved by deploying additional mobile...

Based on the electromagnetism-like algorithm (EM), we propose a novel hybrid learning algorithms which is the improved EM algorithm with genetic algorithm technique (IEMGA) for recurrent fuzzy neural system design. IEMGA are composed of initialization, local search, total force calculation, movement, and evaluation. They are hybridization of EM and GA. EM algorithm is a population-based meta-he...