Sharif Digital Repository

The effectiveness of the local search algorithms for shop scheduling problems is proved frequently. Local search algorithms like tabu search use neighborhood structures in order to obtain new solutions. This paper presents a new neighborhood for the job shop scheduling problem. In this neighborhood, few enhanced conditions are proposed to prevent cycle generation. These conditions allow that the neighborhood encompasses larger number of solutions without increasing the order of computational efforts  

In this paper, we study a resource-constrained project scheduling problem in which a set of project activities have due dates. If the finish time of each one of these activities is not equal to its due date, an earliness or a tardiness cost exists for each tardy or early period. The objective is to minimize the sum of discounted weighted earliness-tardiness penalty costs of these activities. Scatter Search algorithm is used to deal with this extended form of resource-constrained project scheduling problem. Our implementation of Scatter Search integrates the advanced methods such as dynamic updating of the reference set and the use of frequency-based memory within the diversification... 

Large scale Internet services are expected to only increase in complexity and popularity. Their energy consumption is also a major concern in data centers. Smart scheduling of their sub-services on data center Physical Machines (PM) can effectively improve their energy as well as performance. Since today servers are not energy-proportional yet, a major and traditionally neglected source of inefficiency in them is the utilization level of PMs. We present two scheduling algorithms for precedence-constrained parallel Virtual Machines (VM) in a virtualized data center where each VM represents a sub-service of the Internet-scale service. Our algorithms use virtualization technology to increase... 

Time, cost and quality are among the major objectives of any project. In recent years, the demands of project stakeholders regarding reductions in the total cost and time of a project along with achieving the desirable quality of the project have risen significantly. This leads researchers to developing models that incorporate the quality factor to previously existing time-cost trade-off models. This study presents a model for the discrete time-cost-quality trade-off problem. In this model there are a number of execution modes to select for each activity, and the best execution mode (t, c, q) of the activities should be determined to optimize total cost and time objectives, subjected to... 

Correct scheduling of the project is the necessary condition for the project success. In traditional models, the activities duration times are deterministic and known. In real world however, accurate calculation of time for performing each activity is not possible and is always faced with uncertainty. In this paper, the duration of each activity is estimated by the experts as linguistic variables and the said variables are represented in fuzzy numbers form using the fuzzy theory. Estimating the project accomplishment duration and determining the project critical path will be possible through resolving a fuzzy linear programming model. For solving model, Fuzzy Critical Path Method Algorithm... 

The continuous spread of distributed energy resources (DERs) such as combined heating and power (CHP), diesel generators, boilers and renewable energy sources provide an effective solution to energy related problems to serve the power and heat demands with minimum cost. Moreover, the DERs may play a significant role for supplying power and heat in rural areas, where grid electricity is not available. Also, some dry areas may face water scarcity and salinity problems. So, one important solution is the use of DERs to drive desalination units in order to solve water scarcity and salinity problems. In this study, the optimal scheduling of DERs and reverse osmosis (RO) desalination unit that feed... 

One subcategory of project scheduling is the resource constrained project scheduling problem (RCPSP). The present study proposes a differential evolution algorithm for solving the RCPSP making a small change in the method to comply with the model. The RCPSP is intended to program a group of activities of minimal duration while considering precedence and resource constraints. The present study introduces a differential evolution algorithm and local search was added to improve the performance of the algorithm. The problems were then solved to evaluate the performance of the algorithm and the results are compared with genetic algorithm. Computational results confirm that the differential... 

The present paper introduces a novel two-part self-adaptive technique in designing the genetic algorithm for project scheduling problems. One part of the algorithm includes a self-adaptive mechanism for genetic operators like crossover and mutation. The second part contains another self-adaptive mechanism for genetic parameters such as crossover probability. The parts come in turn repeatedly within a loop feeding each other with the information regarding the performance of operators or parameters. The capability of the method is tested and confirmed in comparison to metaheuristic and exact algorithms based on well-known benchmarks  

Project scheduling to maximize the net present value of the cash flows has been a topic of recent research. These researches assume that the duration of activities is known either with certitude or at least with some probability. However, in many applications the structure of the duration of activities is imprecise. In this paper, the project scheduling problem with discounted cash flows under fuzzy environment is considered. The duration of activities are assumed triangular fuzzy numbers. The derived mathematical model is a multi-objective non-linear programming model and for solving it the Taylor expansion is used to transform the objective function to a linear form. To interpret the fuzzy... 

This paper proposes a new approach for solving generation scheduling and ramp rate constrained unit commitment with considering spinning reserve probability. In order to simulate the probability of reserve in the formulation, the estimated probability that spinning reserve is called and generated has been considered. A hybrid heuristic method between genetic algorithm and lambdad iteration method is applied to solve the problem. The proposed approach is applied to two different cases such as a 10-unit base problem without considering probability of reserve and 10-unit problem with considering probability of reserve. The results are compared with other approaches results to exhibit the... 

In this paper resilience oriented water and energy hub scheduling for a remote area is presented. The optimal operation scheduling considering maintenance programming and reliability indices are presented. Demands which include electricity, heat and drinking waters are supplied by diesel generators, boilers, combined heat and power units, and drinking water sources such as desalination units and transferring water. The considered system contains renewable energy resources such as wind turbine and photovoltaic arrays as well as electrical storage units. In order to enhance resiliency of system against forced outages of components and regular maintenance programs, maintenance constraints and... 

Cost optimization for workflow scheduling while meeting deadline is one of the fundamental problems in utility computing. In this paper, a two-phase cost-efficient scheduling algorithm called critical chain is presented. The proposed algorithm uses the concept of slack time in both phases. The first phase is deadline distribution over all tasks existing in the workflow which is done considering critical path properties of workflow graphs. Critical chain uses slack time to iteratively select most critical sequence of tasks and then assigns sub-deadlines to those tasks. In the second phase named mapping step, it tries to allocate a server to each task considering task's sub-deadline. In the... 

Due to the advent of new technologies, devices, and communication tools such as social networking sites, the amount of data produced by mankind is growing rapidly every year. Big data is a collection of large datasets that cannot be processed using traditional computing techniques. MapReduce has been introduced to solve large-data computational problems. It is specifically designed to run on commodity hardware, and it depends on dividing and conquering principles. Nowadays, the focus of researchers has shifted towards Hadoop MapReduce. One of the most outstanding characteristics of MapReduce is data locality-aware scheduling. Data locality-aware scheduler is a further efficient solution to... 

Today, cloud computing has developed as one of the important emergent technologies in communication and Internet. It offers on demand, pay per use access to infrastructure, platforms, and applications. Due to the increase in its popularity, the huge number of requests need to be handled in an efficient manner. Task scheduling as one of the challenges in the cloud computing supports the requests for assigning a particular resource so as to perform effectively. In the resource management, task scheduling is performed where there is the dependency between tasks. Many approaches and case studies have been developed for the scheduling of these tasks. Up to now, a systematic literature review... 

This paper presents a new predictive-reactive rescheduling method for adjusting production schedules in response to the unplanned arrival of new orders in multi-level production. It is based on the concept of dynamic pegging, which enables the reassignment of the Work-In-Progress (WIP) to the existing or newly arrived orders at the time of rescheduling. Extending our previous work on reactive rescheduling with dynamic pegging, the new approach incorporates a probabilistic predictive model of new order arrival in the initial scheduling at the begging of the scheduling horizon. A Mixed Integer Programming (MIP) model is developed for two-phase, predictive-reactive scheduling before and after... 

Optimal scheduling of runway operations plays an important role in improving safety and efficiency of any congested airspace. The objective of scheduling is runway assignment and computing arrival times that minimize delays and maximize runway throughput. Currently, methods for runway scheduling are categorized into First-Come-First-Serve (FCFS) and Constrained Position Shifting (CPS). In this work, we describe a new algorithm for real time scheduling for single as well as multiple parallel runway scheduling. The new approach is comparable to FCFS algorithms in accommodating practical issues while enjoying optimality similar to that of CPS methods. Different case studies show that the new... 

Electric power systems are typically operated at least cost, subject to technical and reliability constraints. This paper presents a probabilistic approach for optimal and reliable scheduling of a competitive electric power market. A competitive structure is proposed which includes a power-pool with centrally optimized scheduling. Ancillary services and transmission management issues are considered in the proposed approach. The value of unit commitment risk is deduced from the generation model. The required generation model is constructed using the outage replacement rate (ORR) of units. The load forecast uncertainty is included in operational risk evaluation. This is due to the increased... 

Satisfying the clients' uncompromising priorities is a challenge for decision makers of organizations that face multiple projects. This paper considers an organization with a multi-skilled workforce working on several predetermined projects under time-of-use energy tariffs where distributed load energy usage is the primary concern of energy suppliers. This paper also considers different time-of-use energy tariffs, which are among the most common strategies to reach a more balanced energy utilization. The problem is stated as a bi-objective mixed-integer programming model containing two conflicting objectives; to minimize the total cost of the multi-skilled workforce and obtain a sustainable... 

The lazy bureaucrat scheduling is a new class of scheduling problems that was introduced in [1]. In these problems, there is one employee (or more) who should perform the assigned jobs. The objective of the employee is to minimize the amount of work he performs and to be as inefficient as possible. He is subject to a constraint, however, that he should be busy when there is some work to do. In this paper, we focus on the cases of this problem where all jobs have the same common deadline. We show that with this constraint, the problem is still NP-hard, and prove some hardness results. We then present a tight 2-approximation algorithm for this problem under one of the defined objective... 

This paper deals with the problem of scheduling bus maintenance activities. The scheduling of maintenance activities is an important component in bus transit operations planning process. The other components include network route design, setting timetables, scheduling vehicles, and assignment of drivers. This paper presents a mathematical programming approach to the problem. This approach takes as input a given daily operating schedule for all buses assigned to a depot along with available maintenance resources. It, then, attempts to design daily inspection and maintenance schedules for the buses that are due for inspection so as to minimize the interruptions in the daily bus operating...