Sharif Digital Repository

In this paper, the tardiness flow shop models with intermediate due date were considered. The flow shop models consist of a set of jobs each having a number of operations, while each operation is performed in a single machine. All the jobs are considered having the same unidirectional precedence order. In the tardiness flow shop models with intermediate due date, which we call the generalized tardiness flow shop models, there exist a due date associated with the completion of each operation, and we want to find a schedule which minimizes the total tardiness of the jobs. This is a more general version of tardiness flow shop in the sense that, by assigning a large value to each of the... 

A lot of projects in real life are subject to some kinds of nonrenewable resources that are not exactly similar to the type defined in the project scheduling literature. The difference stems from the fact that, in those projects, contrary to the common assumption in the project scheduling literature, nonrenewable resources are not available in full amount at the beginning of the project, but they are procured along the project horizon. In this paper, we study this different type of nonrenewable resources. To that end, we extend the resource constrained project scheduling problem (RCPSP) by this resource type (RCPSP-NR) and customize four basic branch and bound algorithms of RCPSP for it,... 

In this research, a permutation flowshop sequence-dependent group scheduling problem with minimisation of total completion time is considered. Since the problem is shown to be strongly NP-hard, a hybrid genetic (HG) algorithm is proposed. The only available lower bounding (LB) method for the proposed research problem in the literature based on branch and price (B&P) algorithm is also enhanced by proposing efficient method to solve sub-problems and proposing a better branching rule. A statistical comparison shows that both the proposed HG algorithm and the proposed LB have better performance than the other methods from the literature with an average 5.96% percentage gap. [Received 13 December... 

This paper presents mathematical modelling of joint lot sizing and scheduling problem in job shop environment under a set of working conditions. The main feature of the problem is to deal with flexible machines able to change their working speeds, known as process compressibility. Furthermore, produced items should be assembled together to make final products. In other words, the products have a multilevel structure, shown with bill of materials. As the problem is proved to be strongly NP-hard, it is solved by a memetic algorithm here. Computational experiences on the data of Mega Motor company are reported. Also, further experiences on random test data confirm the performance of the... 

This paper considers scheduling tasks while minimizing the power consumption of one or more processors, each of which can go to sleep at a fixed cost α. There are two natural versions of this problem, both considered extensively in recent work: minimize the total power consumption (including computation time), or minimize the number of "gaps" in execution. For both versions in a multiprocessor system, we develop a polynomial-time algorithm based on sophisticated dynamic programming. In a generalization of the power-saving problem, where each task can execute in any of a specified set of time intervals, we develop a (1+23α) -approximation, and show that dependence on α is necessary. In... 

In this research, minimizing the expected number of tardy jobs in a dynamic m machine flow-shop scheduling problem, i.e.,FM|r j|E[∑Uj] is investigated. It is assumed that the jobs with deterministic processing times and stochastic due dates arrive randomly to the flow-shop cell. The due date of each job is assumed to be normally distributed with known mean and variance. A dynamic method is proposed for this problem by which the m machine stochastic flow-shop problem is decomposed into m stochastic single-machine sub-problems. Then, each sub-problem is solved as an independent stochastic single-machine scheduling problem by a mathematical programming model. Comparison of the proposed method... 

This paper presents a special case of the general shop called stage shop problem. The stage shop is a more realistic generalization of the mixed shop problem. In the stage shop problem, each job has several stages of operations. In order to solve the stage shop problem with makespan objective function, an existing neighborhood of job shop is used. In this neighborhood, few enhanced conditions are proposed to prevent cycle generation. In addition, a new neighborhood for operations that belong to the same job is presented. These neighborhoods are applied to the stage shop problem in a tabu search framework. A genetic algorithm is used to obtain good initial solutions. An existing lower bound... 

This paper presents mathematical modeling of joint lot sizing and scheduling problem in a job shop environment under a set of realistic working conditions. One main realistic assumption of the current study is dealing with flexible machines able to change their working speeds, known as process compressibility. The production schedules should be subject to limited available time in every planning period. Also, the model assumes that periodical sequences should be determined in a way that they obey from a fixed global sequence. Another complicating aspect of the problem is about consideration of precedence relationships for the needed processes of an item type over the corresponding machines.... 

One of the challenging problems in real-time data-parallel processing applications is to schedule tasks to different servers aiming to increase data locality for higher efficiency or lower delay, and at the same time, doing load balancing to stabilize the system of server-queues. We target this problem, and discuss efficient real-time task scheduling algorithms aimed not only to stabilize the system when the arrival rate is in the capacity region (i.e. throughput optimality condition), but also to minimize the mean delay of all tasks in heavy traffic regime when the arrival rate approaches the capacity boundary (i.e. heavy-traffic optimality condition). In this paper, we point out the data... 

A resource investment problem with discounted cash flows (RIPDCF) is a project-scheduling problem in which (a) the availability levels of the resources are considered decision variables and (b) the goal is to find a schedule such that the net present value of the project cash flows optimizes. In this paper, the RIPDCF in which the activities are subject to generalized precedence relations is first modeled. Then, a genetic algorithm (GA) is proposed to solve this model. In addition, design of experiments and response surface methodology are employed to both tune the GA parameters and to evaluate the performance of the proposed method in 240 test problems. The results of the performance... 

This research considers a project scheduling problem with the object of minimizing weighted earliness-tardiness penalty costs, taking into account a deadline for the project and precedence relations among the activities. An exact recursive method has been proposed for solving the basic form of this problem. We present a new depth-first branch and bound algorithm for extended form of the problem, which time value of money is taken into account by discounting the cash flows. The algorithm is extended with two bounding rules in order to reduce the size of the branch and bound tree. Finally, some test problems are solved and computational results are reported. © 2008 Asian Network for Scientific... 

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.... 

This paper presents the performance analysis of several best-known partitioning scheduling algorithms in real-time and fault-tolerant multiprocessor systems. To do this, multiple versions of tasks are executed on different processors. Both static and dynamic scheduling algorithms are analyzed. In the case of static scheduling algorithms, rate-monotonic (RM) scheduling policy is considered. In the dynamic scheduling algorithms, the scheduling policies are rate-monotonic and earliest-deadline-first (EDF). Partitioning scheduling algorithms which are studied here are heuristic algorithms that are formed by combining any of the bin-packing algorithms with any of the schedulability conditions for... 

In this paper, first a fuzzy random resource-constrained project scheduling problem is presented. The object of the problem is to find the optimal scheduling of project activities. In this model, duration of project activities is a fuzzy random variable. Then, the proposed model is formulated by using the expected value of fuzzy random variables as an IP model. An illustrative example is also provided to clarify the concept. © 2010 World Academic Press, UK. All rights reserved  

Maintenance scheduling of generating units in restructured power systems is a collaborative and interactive process between independent system operators (ISOs) and generating companies (GENCOs). The ISO should comply with GENCO maintenance preferences subject to targeted system reliability levels. This process might be multistage since the admission of all initial unit outage requests may threaten system reliability. Hence, the ISO accepts some proposals and determines alternatives for the remaining units. The GENCOs are then allowed to confirm the alternatives or revise them. In this paper the ISO problem of generating unit maintenance scheduling is tackled. The objective function is to... 

In this paper, we propose a new mathematical programming model to tackle the multi-skilled project scheduling problem. Considering the effect of learning and forgetting on the human skills, an exponential learning function has been developed by assuming the efficiency of employees performing activities to be dynamic. Taking the nonlinearity of the function into account, we use separable programming to acquire an appropriate linear approximation for it. Moreover, the proposed model allows us to relax some of the binary variables linearly without any modifications. At the end, the final model is tested with some instances and is solved by CPLEX in order to confirm the implemented... 

Performability is an important parameter in safety-critical real-time systems. This parameter is defined as the joint consideration of two other important parameters, i.e., reliability and performance. This paper proposes a schedulability condition that guarantees a desired level of performability under various working conditions for real-time systems. The basic idea underlining this condition is to select a subset of schedulable tasks and manage their slack times to satisfy a desired performability level. The proposed condition is evaluated on a hard real-time system that employs the Rate-Monotonic (RM) scheduling algorithm and uses the re-execution mechanism to improve the reliability.... 

Traditionally, the model of a resource-constrained project-scheduling problem (RCPSP) contains a single objective function of either minimizing project makespan or maximizing project net present value (NPV). In order to be more realistic, in this paper, two multi-objective meta-heuristic algorithms of multi-population and two-phase sub-population genetic algorithms are proposed to find Pareto front solutions that minimize the project makespan and maximize the project NPV of a RCPSP, simultaneously. Based on standard test problems constructed by the RanGen project generator, a comprehensive computational experiment is performed, where response surface methodology is employed to tune the... 

In this research, the flexible flowshop sequence-dependent group scheduling problem with minimisation of makespan as the criterion (FFm|fmls, shgi|Cmax) is investigated. A mixed integer linear mathematical model for the research problem is developed. Since the research problem is shown to be NP-hard, a meta-heuristic algorithm based on memetic algorithm (MA) is developed to efficiently solve the problem. Also, a lower bounding technique based on the developed mathematical model is proposed to evaluate the quality of the proposed MA. The performance of the proposed MA is compared with the existing algorithm in the literature, i.e. tabu search (TS), by solving the available test problems in... 

This paper addresses scheduling a set of weighted jobs on a single machine in presence of release date for delivery in batches to customers or to other machines for further processing. The problem is a natural extension of minimizing the sum of weighted flow times by considering the possibility of delivering jobs in batches and introducing batch delivery costs. The classical problem is NP-hard and then the extended version of the problem is NP-hard. The objective function is that of minimizing the sum of weighted flow times and delivery costs. The extended problem arises in a real supply chain network by cooperation between two layers of chain. Structural properties of the problem are...