Sharif Digital Repository

The aim of this study is to show the effectiveness of prohibited operating zone. Generation scheduling is a crucial challenge in power systems especially under new environment of liberalization of electricity industry. This study is focused on the economical aspect of unit commitment problem. Since, the generating units may have certain ranges where operation is restricted based upon physical limitations of machine components or instability. Therefore, Prohibited Operating Zones (POZ) as a redundant constraint is considered, while the next load demand as a very important issue is deliberated. In this study generation scheduling of each hour is conducted by considering the next load demands... 

The integration of various energy supplying systems increases the energy efficiency and energy system reliability. Smart microgrids are an ideal area to use multi-carrier energy systems. In this context, this study presents a novel modelling framework for optimal day-ahead scheduling of a networked multi-carrier energy microgrid (NMCEMG) system. The NMCEMG system in this study is composed of heat, gas, and power supply networks. The presented framework has enhanced the multicarrier microgrid modelling against the previous works that modelled the multi-carrier microgrid as an energy hub due to difficulties in the energy flow analysis of heat and gas networks. The proposed framework optimises... 

Incorporating outsourcing in scheduling is addressed by several researchers recently. However, this scope is not investigated thoroughly, particularly in the job shop environment. In this paper, a new job shop scheduling problem is studied with the option of jobs outsourcing. The problem objective is to minimise a weighted sum of makespan and total outsourcing cost. With the aim of solving this problem optimally, two solution approaches of combinatorial optimisation problems, i.e. mathematical programming and constraint programming are examined. Furthermore, two problem relaxation approaches are developed to obtain strong lower bounds for some large scale problems for which the optimality is... 

Cloud computing is a new framework, which is facing a numerous type of challenges including resource management and energy consumption of data centers. One of the most important duties of cloud service providers is to manage resources and schedule tasks for reducing energy consumption in data centers. In this paper, fuzzy logic is used for finding most adequate DC, improved DVFS algorithm is used for selecting ideal host and developed version of EDF-VD algorithm is utilized for Task scheduling and load balance in cloud computing. Our approach improvement to the current methods including EEVS, DVFS, Homogeneous, MBFD and EEVS-N. © 2019-IOS Press and the authors. All rights reserved  

Cloud computing technology, which is a new model of service provisioning in distributed systems, has been raised as a way to execute workflow applications. To profit from this technology for executing workflow applications, it is necessary to develop workflow scheduling algorithms that consider different QoS parameters such as execution time and cost. Therefore, in this paper, we focus on two criteria: makespan (completion time) and execution cost of workflow application and propose a scheduling algorithm named CB-DT (Constrained Budget-Decreased Time) which aims to create a schedule that decreases the makespan while satisfying the budget constraint of the workflow application. In the... 

Cloud computing is a new framework, which is facing a numerous type of challenges including resource management and energy consumption of data centers. One of the most important duties of cloud service providers is to manage resources and schedule tasks for reducing energy consumption in data centers. In this paper, fuzzy logic is used for finding most adequate DC, improved DVFS algorithm is used for selecting ideal host and developed version of EDF-VD algorithm is utilized for Task scheduling and load balance in cloud computing. Our approach improvement to the current methods including EEVS, DVFS, Homogeneous, MBFD and EEVS-N. © 2019-IOS Press and the authors. All rights reserved  

The growing importance of energy consumption has become an integral part of many decision-making processes in various organizations. In this paper, a framework is proposed for an organization where the undertaken project is implemented by multi-skilled workforce and energy tariffs depending on the time-of-use. This is a real-life situation where energy tariffs are significantly high during the peak demand compared to the one in off peak demand in order to control overloaded consumption of energy. A formulation is developed for the problem to minimize the total cost of consuming required energy. The proposed formulation is validated using several small-scale instances solved by GAMS software.... 

Tackling the dark silicon problem in a heterogeneous multi-core system, the temperature constraints across the system should be addressed carefully by assigning a proper set of tasks to a pool of the heterogeneous cores during the run-time. When such a system is utilized in a reliable/realtime application, the reliability/timing constraints of the application should also be augmented to the temperature constraints and make the tasks mapping problem more and more complex. To solve the mapping problem in such a situation, we propose READY; an online reliability-and deadline-aware mapping and scheduling algorithm for heterogeneous multi-core systems. READY utilizes an adaptive power constraint... 

The rule based scheduling algorithms are a new trend in grid scheduling algorithms; the combination of rule based algorithms for resource selection with various dispatching rules for queuing of jobs can improve or deteriorate their performance. Thus, choosing a proper queuing strategy for each algorithm is a prominent issue in scheduling. In this paper, we introduce two new dispatching rules for resource selection and three new dispatching rules for queuing of jobs; we evaluate the performance of various combinations of these new rule based scheduling algorithms and queuing strategies. Also, we use some major combination of rule based scheduling algorithms with some important queuing... 

Grid scheduling problems are dynamic as the jobs and resources in the system vary overtime. The Rulebased scheduling algorithms are a new trend in grid scheduling which are applicable in dynamic grid environments; The arriving jobs waiting for execution is ordered according to a certain rule and they are dispatched for processing according to that order. Grid scheduling algorithms usually involve more than one objective function. In particular, it is not enough to minimize the Maximum completion time (Makespan) objective function without taking into consideration the lateness of the jobs (Tardiness). In this paper two novel dispatching rules are proposed that aims to minimize the maximum... 

The general approach to fault tolerance in uniprocessor systems is to maintain enough time redundancy in the schedule so that any task instance can be re-executed in presence of faults during the execution. In this paper a scheme is presented to add enough and efficient time redundancy to the Earliest-Deadline-First (EDF) scheduling policy for periodic real-time tasks. This scheme can be used to tolerate transient faults during the execution of tasks. We describe a recovery scheme which can be used to re-execute tasks in the event of transient faults and discuss conditions that must be met by any such recovery scheme. For performance evaluation of this idea a tool is developed. © 2007 IEEE  

Distribution networks are undergoing a fundamental transition due to the expansion of flexible resources as well as renewable energy sources in the system. In this regard, multi-agent structures are developed in modern distribution systems to facilitate the independent operation of local resources. Nevertheless, the non-coordinated operation of independent agents could result in a deviation between the real-time power purchased from transmission network and the day-ahead scheduling. Consequently, this paper aims to provide a novel framework that enables the decentralized management of multi-agent distribution systems, while coordinating the real-time power request and the day-ahead... 

The purpose of this paper is to present a mixed-integer linear programming model for the scheduling problem in an open-shop manufacturing system involving reverse flows, where two job flows (direct and reverse) in two opposite directions are processed on the same machines. The aim is to minimize the maximum completion time of all jobs on all machines (i.e., the makespan). A numerical example is presented and solved using the GAMS software (version 25.1.2) to validate the proposed mathematical model. As this problem is NP-hard, a vibration damping-based optimization (VDO) algorithm is proposed to solve large-scale problems in reasonable execution times. Besides, the Taguchi experimental... 

The purpose of this paper is to present a mixed-integer linear programming model for the scheduling problem in an open-shop manufacturing system involving reverse flows, where two job flows (direct and reverse) in two opposite directions are processed on the same machines. The aim is to minimize the maximum completion time of all jobs on all machines (i.e., the makespan). A numerical example is presented and solved using the GAMS software (version 25.1.2) to validate the proposed mathematical model. As this problem is NP-hard, a vibration damping-based optimization (VDO) algorithm is proposed to solve large-scale problems in reasonable execution times. Besides, the Taguchi experimental... 

The high demand for radiotherapy services, combined with the limited capacity of available resources, patient unpunctuality, and series of appointments, makes Patient Appointment Scheduling (PAS) in radiotherapy centers very challenging. Although most centers use a First-Come-First-Serve (FCFS) policy for appointment scheduling, this approach does not consider patients’ behaviors, and consequently, it performs poorly. This type of inappropriate scheduling usually leads to inefficiency at the center and/or patient dissatisfaction. This study provides a data-driven approach to patient appointment scheduling to deal with the challenges mentioned above, and it considers patients’ histories of... 

In this paper a new predictive-reactive rescheduling method is presented based on the dynamic pegging concept. Scheduling adjustments in a multi-level, mixed-model production system are invoked in response to the unplanned events, such as new order arrival, changes in due dates, and order cancellation. By using the dynamic pegging approach at the time of rescheduling, Work-In-Progress (WIP) can be reassigned to the existing or new orders. Based on our previous work on reactive-only rescheduling with dynamic pegging, a Mixed Integer Programming (MIP) model is developed for predictive-reactive scheduling of new orders of different product types that arrive following exponential distribution. A... 

The application of mathematical and systematic models and approaches to health is on the rise. In this study, a mixed-integer linear programming problem with cost (staff payroll) objective function is proposed to determine homogeneous personnel shift scheduling so that the constraints of the number of personnel per shift are met. The purpose of this study is to optimize the scheduling of personnel with the same skills to minimize variable hospital costs. In a hospital, homogeneous personnel might be skilled nurses who can work in the same departments or service staff of the departments. First, a mathematical model is proposed for scheduling as a linear problem and solved using Lingo...