Sharif Digital Repository

The three-dimensional multiple bin-size bin packing problem (3D-MBSBPP) has many practical applications in the logistic problems such as warehouse management, transportation planning and container loading. An efficient solution to the problem can have significant effects on reducing the transportation costs, improving the status and increasing the productivity and profitability of the companies. The mathematical models proposed for this problem are few in number and can, therefore, be expanded and improved much further. In this paper, based on the needs of a spare-part company in Iran, we developed a mathematical model for 3D-MBSBPP. This model takes into account the rotation of the boxes... 

Multi-Facility Weber Problem (MFWP), also known as continuous location–allocation problem, entails determining the locations of a predefined number of facilities in a planar space and their related customer allocations. In this paper, we focus on a new variant of the problem known as Single-Source Capacitated MFWP (SSCMFWP). To tackle the problem efficiently and effectively, an iterative two-phase heuristic algorithm is put forward. At the phase I, we aim to determine proper locations for facilities, and during the phase II, assignment of customers to these facilities is pursued. As an alternative solution method, a simulated annealing (SA) algorithm is also proposed for carrying out the... 

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... 

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... 

In this paper, a new algorithm for solving the shortest loop design problem is presented. The shortest loop design problem is to find the shortest loop for an automated guided vehicle covering at least one edge of each department of a block layout. In this paper, first it is shown that this problem can be represented as a graph model. The properties of the presented model enable us to design a meta-heuristic based on ant colony system algorithm for solving the shortest loop design problem. Computational results show the efficiency of our algorithm in compare to the other techniques  

In this paper transmission network planning will be presented in which the competition ability associated with minimum investment costs is considered. This type of transmission expansion can be addressed as an open access transmission expansion planning. Such open access transmission planning is modeled regarding extreme and feasible generating scenarios. A mathematical modeling of transmission expansion problem, considering generation scenarios is solved via a constructive heuristic algorithm using an iterative technique. In this paper a constructive heuristic algorithm solves several non-linear programming in order to identify the most important transmission line that should be... 

Non-Convex Economic Dispatch (NED) has been addressed as an open and demanding optimization problem in power systems. Due to the fact that realistic ED problems have non-convex cost functions with equality and inequality constraints, conventional search methods are unable to effectively find the global solution. In recent years, because of their great potential to achieve optimal or close-to-optimal solution, meta-heuristic optimization techniques have attracted significant attention to tackle the complexity of NED problems. In this paper, an efficient approach is proposed based on Imperialist Competitive Algorithm (ICA). The proposed algorithm named multi-operator ICA (MuICA) merges the... 

In this research, a maximal covering location problem (MCLP) with real-world constraints such as multiple types of facilities and vehicles with different setup costs is taken into account. An original mixed integer linear programming (MILP) model is constructed in order to find the optimal solution. Since the problem at hand is shown to be NP-hard, a constructive heuristic method and a meta-heuristic approach based on genetic algorithm (GA) are developed to solve the problem. To find the most effective solution technique, a set of problems of different sizes is randomly generated and solved by the proposed solution methods. Computational results demonstrate that the heuristic method is... 

Clustering the web documents is one of the most important approaches for mining and extracting knowledge from the web. Recently, one of the most attractive trends in clustering the high dimensional web pages has been tilt toward the learning and optimization approaches. In this paper, we propose novel hybrid harmony search (HS) based algorithms for clustering the web documents that finds a globally optimal partition of them into a specified number of clusters. By modeling clustering as an optimization problem, first, we propose a pure harmony search-based clustering algorithm that finds near global optimal clusters within a reasonable time. Then, we hybridize K-means and harmony clustering... 

The optimization of chemical syntheses based on superstructure modeling is a perfect way for achieving the optimal plant design. However, the combinatorial optimization problem arising from this method is very difficult to solve, particularly for the entire plant. Relevant literature has focused on the use of mathematical programming approaches. Some research has also been conducted based on meta-heuristic algorithms. In this paper, two approaches are presented to optimize process synthesis superstructure. Firstly, mathematical formulation of a superstructure model is presented. Then, an ant colony algorithm is proposed for solving this nonlinear combinatorial problem. In order to ensure... 

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... 

This paper presents a simulation-based optimization approach for railway timetabling, which is made interesting by the need for trains to stop periodically to allow passengers to pray. The developed framework is based on integration of a simulation model and an evolutionary path re-linking algorithm with the capability of scheduling trains, subject to the capacity constraints in order to minimize the total waiting times. A customized deadlock avoidance method has been developed which is based on a conditional capacity allocation. The proposed look-ahead deadlock avoidance approach is effective and easy to implement in the simulation model. A case study of the Iranian Railway (RAI) is... 

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... 

This paper presents an event-driven simulation-based optimization method for solving the train timetabling problem to minimize the total traveling time in the hybrid single and double track railway networks. The simulation approach is well applied for solving the train timetabling problems. In present simulation model, the stations and block sections of the railway network are respectively considered as the nodes and edges of the network model. The developed software named SIMARAIL has the capability of scheduling trains in large scale networks respecting the capacity constraints and infrastructure characteristics. This simulation model for railway timetabling is based on a detailed... 

The focus of this research is on the flexible flow shop sequence dependent group scheduling problem (FFSDGS) with minimization of makespan as the criterion (FFm|fmls, Splk|Cmax). Since the research problem is shown to be NP-hard, a meta-heuristic algorithms based on memetic algorithm is developed to efficiently solve the problem. The performance of the proposed algorithm is compared with the only available meta-heuristic algorithm in the literature, i.e., tabu search (TS). The comparison is performed based on paired t-test and the result shows that the memetic algorithm has a superior performance compared to the TS  

Meta-heuristic algorithms have been successfully applied to solve the redundancy allocation problem in recent years. Among these algorithms, the electromagnetism-like mechanism (EM) is a powerful population-based algorithm designed for continuous decision spaces. This paper presents an efficient memory-based electromagnetism-like mechanism called MBEM to solve the redundancy allocation problem. The proposed algorithm employs a memory matrix in local search to save the features of good solutions and feed it back to the algorithm. This would make the search process more efficient. To verify the good performance of MBEM, various test problems, especially the 33 well-known benchmark instances in...