Virtual power plant (VPP) is an effective approach to aggregate distributed generation resources under a central control. This paper introduces a mixed-integer linear programming model for optimal scheduling of the internal resources of a large scale VPP in order to maximize its profit. The proposed model studies the effect of a demand response (DR) program on the scheduling of the VPP. The pro...

This paper aims to develop a multi-objective model for scheduling cargo trains faced by the costs of tardiness and earliness, time limitations, queue priority and limited station lines. Based upon the Islamic Republic of Iran Railway Corporation (IRIRC) regulations, passenger trains enjoy priority over other trains for departure. Therefore, the timetable of cargo trains must be determined based...

In traditional scheduling literature, it is generally assumed that the location of facilities are predetermined and fixed in advance. However, these decisions are interrelated and may impact each other significantly. Therefore finding a schedule and facility location has become an important problem as an extension of the well-known scheduling problems. In this research we consider joint decisio...

This paper presents a novel, integer-linear programming (ILP) model for an identical parallel-machine scheduling problem with family setup times that minimizes the total weighted flow time (TWFT). Some researchers have addressed parallel-machine scheduling problems in the literature over the last three decades. However, the existing studies have been limited to the research of independent jobs,...

This paper presents a decision making approach for mid-term scheduling of large industrial consumers based on the recently introduced class of Stochastic Dominance (SD)- constrained stochastic programming. In this study, the electricity price in the pool as well as the rate of availability (unavailability) of the generating unit (forced outage rate) is considered as uncertain parameters. Th...

In this paper, we first introduce a generalized version of open shop scheduling (OSS), called generalized cyclic open shop scheduling (GCOSS) and then develop a hybrid method of metaheuristic to solve this problem. Open shop scheduling is concerned with processing n jobs on m machines, where each job has exactly m operations and operation i of each job has to be processed on machine i . However...

Cloud computing is the latest technology that involves distributed computation over the Internet. It meets the needs of users through sharing resources and using virtual technology. The workflow user applications refer to a set of tasks to be processed within the cloud environment. Scheduling algorithms have a lot to do with the efficiency of cloud computing environments through selection of su...

In this paper, we proposed an algorithm for solving the problem of task scheduling using particle swarm optimization algorithm, with changes in the Selection and removing the guide and also using the technique to get away from the bad, to move away from local extreme and diversity. Scheduling algorithms play an important role in grid computing, parallel tasks Scheduling and sending them to ...

Recently, fog computing has been introducedto solve the challenges of cloud computing regarding Internet objects. One of the challenges in the field of fog computing is the scheduling of tasks requested by Internet objects. In this study, a review of articles related to task scheduling in fog computing has been done. At first, the research questions and goals will be introduced, an...