In scheduling problems, it is often assumed that all machines are available during scheduling horizon. Clearly, a machine may not be available due to breakdown or performing maintenance activities. This paper considers a multiple-route job shop configuration, where each part has multiple routes to be produced. In this context, the problem of scheduling jobs together with a set of pre-defined maintenance activities is of interest. Due to the complexity of the problem, no exact mathematical approach can yield solution in reasonable amount of time and, thus, applying heuristic approach is suggested. In this paper, the problem is first formulated as a 0-1 non-linear integer program. Then an approach based on artificial immune system is proposed to tackle the complexity of the problem. In order to evaluate the performance of the proposed approach 30 cases are designed and solved using the proposed approach and Lingo software. The results show that the proposed approach can obtain good solutions in reasonable time.

Highway construction projects are one of the most important construction projects in the world. Therefore predicting the time of these kinds of projects is important. Basically highway projects are including few activities which are repeating along the horizontal direction. One of the best methods for scheduling these types of projects is linear scheduling method. The repetitive nature of the highway activities is a good reason for schedulers to use linear scheduling methods in order to estimate the time of the project. One of the most important factors in linear projects is considering the effect of the activities productivity on scheduling. The first part of the research has been proposed to quantify the main equation of the identified factors for predicting the daily production rates of the embankment activity. The second part is scheduling the highway construction projects by developing the LSMvpr method based on the application of the embankment activity productivity equation. The purpose of the research is to develop the LSMvpr method for scheduling the highway construction projects by considering the concept of activity productivity in the shape of an equation varying by independent variables changes. By the use of multiple regression analysis the coefficients of affecting factors have been calculated in order to gain a production rate equation for predicting the embankment activity productivity. A software package has been presented for scheduling a highway construction project by coding in MATLAB. The offered software used for validating the model for scheduling the highway construction projects.

In this paper we present a unified (probabilistic/possibilistic) model for resource-constrained project scheduling problem (RCPSP) with uncertain activity durations and a concept of a heuristic approach connected to the theoretical model. It is shown that the uncertainty management can be built into any heuristic algorithm developed to solve RCPSP with deterministic activity durations. The essence and viability of our unified model are illustrated by fuzzy examples presented in the recent fuzzy RCPSP literature.

This paper studies the multi-project scheduling problem which involves multiple projects with different importance weight; with predefined assigned due dates; with activities that have uncertain durations; and with renewable resources that are constrained. The resource sharing policy is applied to share the resources among projects. Due to the environmental rapid changes and also the uniqueness of projects, the probability distribution function of uncertain durations cannot be estimated with confidence. Besides, the multi-project scheduling problem with its large scale investment dictates a conservative approach to deal with the existing uncertainty. Therefore, the Robust Resource-Constrained Multi-Project Scheduling Problem (RRCMPSP) is studied in this paper while the maximum total weighted tardiness of the projects should be minimized. A scenario-relaxation algorithm is implemented which results in optimal solutions for the RRCMPSP. The aim is to find an optimal structure containing all the projects in such a way that it transfers the resources between the activities based on the resource sharing policy while the maximum weighted differences between the projects finish times and their assigned due dates will be minimum.

The resource-constrained project scheduling problem is to find a schedule that minimizes the project duration subject to precedence relations and resource constraints. To further account for economic aspects of the project, one may add an objective of cash nature to the problem. In addition, dynamic nature and variations in real world are known to introduce uncertainties into data. Therefore, this study is aimed at proposing a multi-objective model for resource-constrained project scheduling problem, with the model objectives being to minimize makespan, and maximize net present value of the project cash flows; the proposed model has activity times expressed in fuzzy numbers where the corresponding uncertainties are taken into account. The project environment is considered to be a multi-resource environment where more than one resource is needed for the execution of any activity. Also, the proposed model comes with time lags in precedence relations between activities. The proposed model is validated by using epsilon-constraint method. The α-cut approach as well as the expression of acceptable risk level by the project manager is used to defuzzificate fuzzy activity durations. Since the problem is NP-hard, a NSGA-II meta-heuristic algorithm is proposed to solve the problem. The algorithm performance has been evaluated in terms of different criteria.

Background and Objective: Nowadays, the saliency of workload has become more apparent in ergonomic studies. Workload can cause incident since it is directly related to unsafe situations at work. Therefore, it is important to measure workload in different occupations. This study was conducted to evaluate the validity and reliability of driver activity load index questionnaire for assessing the mental load of drivers. Materials and Methods: This cross-sectional and descriptive-analytic study was conducted on 100 bus drivers operating in one of the manufacturing companies. The validity of the questionnaire was evaluated by academic and queue experts (lay experts). Additionally the reliability of this index was measured through employing Cronbach's alpha and intra-cluster correlation test on the data obtained from 10 participants. Data were analyzed using SPSS (version 18) software. Results: The mean age of participants was 50. 8 years with the standard deviation of 8. 29. Furthermore, the mean of work experience among drivers was 22. 18 years. The outcome of the Cronbach’ s alpha coefficient revealed that the reliability of the questionnaire was higher than 0. 7. Furthermore, intra-cluster correlation coefficient of the questionnaire was estimated higher than 0. 7 in all factors affecting the interference factor. The obtained results were indicative of moderate and optimum level of reliability. Conclusion: According to the results of validity and reliability indices, the driver activity load index questionnaire can be used as a valid and reliable questionnaire in Iran to examine and measure the mental load of drivers.

Task graph scheduling is a multi-objective optimization and NP-hard problem. In this paper a new algorithm on homogeneous multiprocessors systems is proposed. Basically, scheduling algorithms are targeted to balance the two parameters of time and energy consumption. These two parameters are up to a certain limit in contrast with each other and improvement of one causes reduction in the other one. The problem is to achieve the trade-off between these two parameters. Pre-scheduling algorithms are mainly aimed at modifying the structure of task graph to gain optimal scheduling.In the proposed algorithm the suitable number of processors for scheduling the task graph is computed. The idea of Nash equilibrium is mainly applied to compute the appropriate number of processors in such a way that the idle time of the processors is reduced while their processing power is increased. Also, considering the communication costs and interdependencies, the tasks are merged as their earliest start time is reduced. In this way, the length of the critical path is reduced while the degree of parallelism is increased and ultimately the completion time is reduced. Our experimental result on a number of known benchmark graphs demonstrates the effect of our proposed algorithm.