Sharif Digital Repository

In this paper, the joint problem of project selection and project scheduling under uncertain environment is formulated, analyzed, and solved by multistage stochastic programs. First of all, a general mathematical formulation which can address several versions of the problem is presented. A multi-period project selection and scheduling problem is introduced and modeled by multistage stochastic programs, which are effective for solving long-term planning problems under uncertainty. A set of scenarios and corresponding probabilities is applied to model the multivariate random data process (costs or revenues, available budget, chance of success). Then, due to computational complexity, a scenario... 

In this paper, we have developed a production planning and marketing model in unreliable flexible manufacturing systems with inconstant demand rate that its rate depends on the level of advertisement on that product. The proposed model is more realistic and useful from a practical point of view. The flexible manufacturing system is composed of two machines that produce a single product. Markovian models frequently have been used in modeling a wide variety of real-world systems under uncertainties. Therefore, in this paper, the inventory balance equation is represented by a continuous-time model with Markov jump process to take into account machines breakdown. The objective is to minimize the... 

Original scientific paper Developing a model for citizens' satisfaction with public services is one of the effective factors for improvement of service quality. In recent years, many studies have been carried out to identify a model for citizens' satisfaction with public sector services. In the structure of the presented models in the literature, one of the most important issues regarding organizations giving public services is identification of service scopes that have the most impact on citizens' satisfaction. This paper aims to develop a model to identify citizens' satisfaction status with public services. To do so, first, key factors influencing citizens' satisfaction with public... 

The job shop scheduling problem is a difficult combinatorial optimization problem. This paper presents a hybrid algorithm which combines global equilibrium search, path relinking and tabu search to solve the job shop scheduling problem. The proposed algorithm used biased random sampling to have a better covering of the solution space. In addition, a new version of N6 neighborhood is applied in a tabu search framework. In order to evaluate the algorithm, comprehensive tests are applied to it using various standard benchmark sets. Computational results confirm the effectiveness of the algorithm and its high speed. Besides, 19 new upper bounds among the unsolved problems are found  

In this paper the setup assembly line balancing and scheduling problem (SUALBSP) is considered. Since this problem is NP-hard, a hybrid genetic algorithm (GA) is proposed to solve the problem. This problem involves assigning the tasks to the stations and scheduling them inside each station. A simple permutation is used to determine the sequence of tasks. To determine the assignment of tasks to stations, the algorithm is hybridized using a dynamic programming procedure. Using dynamic programming, at any time a chromosome can be converted to an optimal solution (subject to the chromosome sequence). Since population diversity is very important to prevent from being trapped in local optimum... 

The job shop scheduling problem with makespan criterion is valuable from both practical and theoretical points of view. This problem has been attacked by most of the well-known meta-heuristic algorithms. Among them, tabu search has emerged as the most effective approach. The proposed algorithm takes advantages of both N1 and N6 neighborhoods. N1 neighborhood is used as a path relinking procedure while N6 neighborhood with its guideposts is applied in a tabu search framework. In addition, a method is presented for updating the topological order, heads and tails in N6 neighborhood. The algorithm is tested on standard benchmark sets, outperformed all previous approaches (include i-TSAB) and... 

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  

This paper presents stage shop problem which is a special case of the general shop. 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, a tabu search algorithm is developed. In addition, an existing lower bound of the job shop is adapted to the new problem and the computational results have been compared to it. The proposed TS algorithm has reached the optimal solutions for about half of the problem instances  

Multistage stochastic programs are effective for solving long-term planning problems under uncertainty. Multi-period project portfolio selection problems can be modeled by multistage stochastic programs. These models utilize a set of scenarios and corresponding probabilities to model the multivariate random data process (costs or revenues, available budget, chance of success). For most practical problems, the optimization problem that contains all possible scenarios is too large. Due to computational complexity, this program is often approximated by a model involving a (much) smaller number of scenarios. The scenario reduction algorithms determine a subset of the initial scenario set and... 

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... 

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... 

This paper presents a special case of the general shop called partial job shop problem. The partial job shop is a more realistic generalization of the mixed shop problem. The problem is formulated as a mixed integer programming model. A scatter search algorithm combined with tabu search and path relinking is used to tackle this problem with makespan criterion. The computational experiments are performed on some problem instances. The results are compared with a lower bound and the effectiveness of the algorithm is shown  

Purpose - This paper aims to address the capability of reliability-centered maintenance (RCM), which is a preventive maintenance design tool. Design/methodology/approach - A model named Plant Function Deployment (PFD) is developed, in which the methodology of quality function deployment (QFD) is added to RCM to improve RCM capability in preserving the functions of the plants. Findings - The objective of preserving the plant functions with least resources, in RCM, is attained more efficiently if the methodology of QFD is added to RCM. Practical implications - PFD is a model for designing a preventive maintenance program which uses RCM and QFD methodologies. PFD organizes all the important... 

This paper deals with the resource-constrained project scheduling problem with flexible work profiles. In this problem, a project contains activities interrelated by finish-start-type precedence constraints with a time lag of zero. In many real-life projects, however, it often occurs that only one renewable bottleneck resource is available and that activities do not have, a fixed prespecified duration and associated resource requirement, but a total work content, which essentially indicates how much work has to be performed on them. Based on this work content, all feasible work profiles have to be specified for the activities, each characterized by a, fixed duration and a resource... 

Given the importance of crude oil prices for businesses, governments and policy makers, this paper investigates predictability of oil prices using artificial neural networks taking into account the exhaustible nature of crude oil and impact of monetary policy along with other major drivers of crude oil prices. A multilayer perceptron neural network is developed and trained with historical data from 1980 to 2014 and using mean square error for testing data, optimal number of hidden layer neurons is determined and the designed MLP neural network is used for estimation of the forecasting model. Meanwhile, an economic model for crude oil prices is developed and estimated using a vector... 

Recently, with the expansion of environmental issues and raising of customers' awareness, companies are experiencing huge pressure from shareholders and the government for greater compatibility with their environment. Companies and industry owners must implement green operations in their daily activities to be able to keep up with the competitive atmosphere of the environment. One of the most important operations to be implemented is cooperating with green suppliers. In this study, a multi-objective mathematical model is proposed to select suppliers and allocate optimal orders to them in a two-echelon supply chain, including supply and distribution echelons. The proposed model focuses on the... 

This paper is concerned with the study of the constant due-date assignment policy in a multistage assembly system. The multistage assembly system is modeled as an open queueing network. It is assumed that the product order arrives according to a Poisson process. In each service station, there is either one or infinite machine with exponentially distributed processing time. The transport times between every pair of service stations are independent random variables with generalized Erlang distributions. It is assumed that each product has a penalty cost that is some linear function of its due-date and its actual completion time. The due date is found by adding a constant to the time that the... 

An optimal algorithm based on branch-and-bound approach is presented in this paper to determine lot sizes for a single item in material requirement planning environments with deterministic time-phased demand and constant ordering cost with zero lead time, where all-units discounts are available from vendors and backlog is not permitted. On the basis of the proven properties of optimal order policy, a tree-search procedure is presented to construct the sequence of optimal orders. Some useful fathom rules have been proven, which make the algorithm very efficient. To compare the performance of this algorithm with the other existing optimal algorithms, an experimental design with various... 

In this paper, a new hybrid metaheuristic algorithm based on the scatter search approach is developed to solve the well-known resource-constrained project scheduling problem. This algorithm combines two solutions from scatter search to build a set of precedence feasible activity lists and select some of them as children for the new population. We use the idea presented in the iN forward/backward improvement technique to define two types of schedule, direct and reverse, and the members of the sequential populations change alternately between these two types of schedule. Extensive computational tests were performed on standard benchmark datasets and the results are compared with the best... 

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...