Sharif Digital Repository

This paper presents a new method for restoration of distribution networks after a fault occurrence. This problem is solved from the viewpoint of the distribution system operator with the main goal of minimizing the operating cost during the fault clearance period. The effects of distributed generation (DG) units and direct load control (DLC) programs are considered in designing the proposed restoration procedure. Moreover, the uncertainties associated with the predicted loads of different nodes and the availability of DG are modeled here. Robust optimization is used to model the uncertainties of restoration problems and manage their associated risks. Finally, a robust reconfiguration plan is... 

The use of traffic information in the form of radio reports, as a solution to the problem of congestion, is one of the issues, which are of particular importance for large cities like Tehran. In this study, factors affecting the use of traffic information in the context of a developing country are examined for commuters in the city of Tehran using ordered logit models. Results based on the particular survey designed for this purpose are compared to those of a developed country. Regarding the use of information in the form of listening to the radio traffic reports, the models show that older commuters, commuters who adjust their departure time according to traffic conditions (those who are... 

This paper presents an optimisation model for polymer electrolyte membrane fuel cell system based on simultaneous power maximisation and cost minimisation. The results show that, by employing appropriate relation between the objectives, the innovative design could be proposed. Genetic algorithm is applied to solve the optimisation problem. Power maximisation results reveal that at maximum amount of power (1.95 kW), unit cost of energy is $0.64. In contrast, minimisation of cost decreases unit cost of energy to $0.33. In this condition, output power is reduced approximately to 0.93 kW. To consider both optimisation problems concurrently, weighting method and Pareto set are employed. Our... 

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... 

The problem of this paper deals with the multi-mode project scheduling problem under uncertainty of activity duration where only the renewable resources are taken into account and a given deadline has to be met at the cost of recruiting additional resources. A heuristic algorithm is employed to solve this problem, and to maintain the robustness of the baseline schedule, the concept of critical chain project management (CCPM) is applied in which a new definition to resource buffer is considered. A simulation methodology is used to determine the size and location of resource buffers in the schedules in which three different buffer sizes and three different uncertainty levels are considered.... 

Simulation optimization is an endeavor to determine the best combination of inputs that result in the best system performance criterion without evaluating all possible combinations. Since simulation optimization applies to many problems, it is extensively studied in the literature with different methods. However, most of these methods ignore the uncertainty of the systems’ parameters, which may lead to a solution that is not robustly optimal in reality. Motivated by this uncertainty, we propose a robust simulation optimization algorithm that follows the well-known Taguchi standpoint but replaces its statistical technique with a minimax method based on the kriging (Gaussian process)... 

Simulation optimization is an endeavor to determine the best combination of inputs that result in the best system performance criterion without evaluating all possible combinations. Since simulation optimization applies to many problems, it is extensively studied in the literature with different methods. However, most of these methods ignore the uncertainty of the systems’ parameters, which may lead to a solution that is not robustly optimal in reality. Motivated by this uncertainty, we propose a robust simulation optimization algorithm that follows the well-known Taguchi standpoint but replaces its statistical technique with a minimax method based on the kriging (Gaussian process)... 

Primal-dual interior-point methods (IPMs) have shown their power in solving large classes of optimization problems. However, there is still a discrepancy between the practical behavior of these algorithms and their theoretical worst-case complexity results with respect to the update strategies of the duality gap parameter in the algorithm. Recently, this discrepancy was significantly reduced by Peng, J., Roos, C. and Terlaky, T., 2002, Self-Regularity: A New Paradigm for Primal-Dual Interior-Point Algorithms (Princeton, NJ: Princeton University Press) who introduced a new family of self-regular (SR)-proximity functions based IPMs. In this paper, based on a class of SR proximities, we propose... 

In this paper, the flexible flow shop sequence-dependent group scheduling problem (FFSDGS) with minimisation of makespan as the criterion (FF m|fmls, S plk|C max) is investigated. For the first time a mathematical model for the proposed research problem is developed. Since the problem is shown to be NP-hard, six metaheuristic algorithms based on tabu search (TS) are developed to efficiently solve the problem. The proposed metaheuristics are different to the only available metaheuristic algorithm in the literature based on TS. By applying randomised complete block design and using available test problems in the literature, the best of the proposed TS algorithms in this research is identified.... 

We consider a multi-facility location problem in the presence of a line barrier with the starting point of the barrier uniformly distributed. The objective is to locate n new facilities among m existing facilities minimising the summation of the weighted expected rectilinear barrier distances of the locations of new facilities and new and existing facilities. The proposed problem is designed as a mixed-integer nonlinear programming model, conveniently transformed into a mixed-integer quadratic programming model. The computational results show that the LINGO 9.0 software package is effective in solving problems with small sizes. For large problems, we propose two meta-heuristic algorithms,... 

Additive manufacturing (AM), is a new technology for the manufacturing of the physical parts through an additive manner. In the AM process, the orientation pattern of the part is an important variable that significantly influences the product properties such as the build time, the surface roughness, the mechanical strength, the wrinkling, and the amount of support material. The build time and the surface roughness are the more important criteria than others that can be considered to find the optimum orientation of parts. The designers and manufacturing engineers usually attempt to find an optimum solution to reach the product with high quality at the minimum time. Determining the optimum... 

Motivated by the bus escape routing problem in printed circuit boards, we revisit the following problem: given a set of n axis-parallel rectangles inside a rectangular region R, find the maximum number of rectangles that can be extended toward the boundary of R, without overlapping each other. We provide an efficient algorithm for solving this problem in O(n2 log3 n log log n) time, improving over the current best O(n3)-time algorithm available for the problem  

In the touring polygons problem (TPP), for a given sequence (s= P0, P1, ⋯, Pk, t = Pk+1) of polygons in the plane, where s and t are two points, the goal is to find a shortest path that starts from s, visits each of the polygons in order and ends at t. In the constrained version of TPP, there is another sequence (F0, ⋯, Fk) of polygons called fences, and the portion of the path from Pi to Pi+1 must lie inside the fence Fi. TPP is NP-hard for disjoint non-convex polygons, while TPP and constrained TPP are polynomially solvable when the polygons are convex and the fences are simple polygons. In this work, we present the first polynomial time algorithm for solving constrained TPP when the... 

The pipe-spool fabrication process is a critical operational section in the piping projects that usually used to accelerate and discipline the installation process, especially, when we have a particular deadline for the project. For this reason, the fast and optimal scheduling of the fabrication activities with considering the real conditions and using manual or traditional methods is a significant problem for the decision-makers. In this paper, we use a novel linear programming model to schedule the spool fabrication activities based on the flexible job shop scheduling problem (FJSP). Because FJSP is a challengeable NP-hard problem, we solve the proposed mathematical model with a heuristic... 

A bi-objective stochastic capacitated multi-facility location–allocation problem is presented where the customer demands have Bernoulli distributions. The capacity of a facility for accepting customers is limited so that if the number of allocated customers to the facility is more than its capacity, a shortage will occur. The problem is formulated as a bi-objective mathematical programming model. The first objective is to find optimal locations of facilities among potential locations and optimal allocations of stochastic customers to the facilities so that the total sum of fixed costs of establishment of the facilities and the expected values of servicing and shortage costs is minimized. The... 

This paper proposes a multi-item economic order quantity model with imperfect items in supply deliveries. The inspection process to classify the items is not perfect and involves two types of error: Type-I and Type-II. To cope with the uncertainty involved in real-world applications and to bring the problem closer to reality, operational constraints are assumed stochastic. The aim is to determine the optimal order and back order sizes of the items in order to achieve maximum total profit. As the proposed mathematical model is a constrained nonlinear programming, three different solution methods including an exact method named the interior-point and two novel meta-heuristics named grey wolf... 

Recently, Ghanbari and Mahdavi-Amiri (Appl Math Model 34:3363–3375, 2010) gave the general compromised solution of an LR fuzzy linear system using ABS algorithm. Here, using this general solution, we solve quadratic programming problems with fuzzy LR variables. We convert fuzzy quadratic programming problem to a crisp quadratic problem by using general solution of fuzzy linear system. By using this method, the crisp optimization problem has fewer variables in comparison with other methods, specially when rank of the coefficient matrix is full. Thus, solving the fuzzy quadratic programming problem by using our proposed method is computationally easier than the solving fuzzy quadratic... 

Macro-operators are sequences of actions that can guide a planner to achieve its goals faster by avoiding search for those sequences. However, using macro-operators will also increase the branching factor of choosing operators, and as a result making planning more complex and less efficient. On the other hand, the detection and exploitation of symmetric structures in planning problems can reduce the search space by directing the search process. In this paper, we present a new method for detecting symmetric objects through subgraph-isomorphism, and exploiting the extracted information in macrooperator selection. The method has been incorporated into HSP2, and tested on a collection of...