Sharif Digital Repository

In this paper, a seasonal multi-product multi-period inventory control problem is modeled in which the inventory costs are obtained under inflation and all-unit discount policy. Furthermore, the products are delivered in boxes of known number of items, and in case of shortage, a fraction of demand is considered backorder and a fraction lost sale. Besides, the total storage space and total available budget are limited. The objective is to find the optimal number of boxes of the products in different periods to minimize the total inventory cost (including ordering, holding, shortage, and purchasing costs). Since the integer nonlinear model of the problem is hard to solve using exact methods, a... 

Clustering is the process of grouping data objects into set of disjoint classes called clusters so that objects within a class are highly similar with one another and dissimilar with the objects in other classes. The k-means algorithm is a simple and efficient algorithm that is widely used for data clustering. However, its performance depends on the initial state of centroids and may trap in local optima. In order to overcome local optima obstacles, a lot of studies have been done in clustering. The Fashion Algorithm is one effective method for searching problem space to find a near optimal solution. This paper presents a hybrid optimization algorithm based on Generalized Fashion Algorithm... 

The concept of smart grid (SG) has been introduced to improve the operation of the power systems. In modern structures of power systems, different reasons prompt researchers to suggest integrated analysis of multi-carrier energy systems. Considering synergy effects of the couplings between different energy carriers and utilising intelligent technologies for monitoring and controlling of energy flow may change energy system management in the future. In this paper, we propose a new solution which is entitled smart energy hub (SEH) that models a multi-carrier energy system in a SG. SEH solutions allow homeowners to manage their energy consumption to reduce their electricity and gas bill. We... 

This paper addresses dynamic cell formation problem (DCFP) which has been explored vastly for several years. Although a considerable body of literature in this filed, two remarkable aspects have been significantly ignored so far, as uncertainty and human-related issues. In order to compensate such a shortage, this paper develops a bi-objective stochastic model. The first objective function of the developed model seeks to minimize total cost of machine procurement, machine relocation, inter-cell moves, overtime utilization, worker hiring/laying-off, and worker moves between cells; while the second objective function maximizes labor utilization of the cellular manufacturing system. In the... 

This paper presents a stochastic framework to properly involve the uncertainties associated with demand in distribution system restoration (DSR) problem. To reach this goal, these uncertainties are represented as probabilistic scenarios corresponding to different load levels. Subsequently, the associated stochastic optimization problem is formulated such that it can be readily solved using dynamic programming approach. Moreover, a clustering technique is presented that enables the dynamic programming approach to find near-optimal solutions for the stochastic load restoration problem with reasonable computational effort. The proposed framework is implemented on a real-world test system, and... 

A production-routing problem with price-dependent demand (PRP-PD) is studied in this paper. Demand follows a general convex, differentiable, continuous and strictly decreasing function in price. The problem is modeled as a mixed integer nonlinear program (MINLP). Two Outer Approximation (OA) based algorithms are developed to solve the PRP-PD. The efficiency of the proposed algorithms in comparison with commercial MINLP solvers is demonstrated. The computational results show that our basic OA algorithm outperforms the commercial solvers both in solution quality and in computational time aspects. On the other hand, our extended (two-phase) OA algorithm provides near-optimal solutions very... 

Hardware/Software (HW/SW) partitioning plays one of the most important roles in Co-design of embedded systems that is due to made at the beginning of the cycle of the design. The ultimate designed system's performance strongly depends on partitioning. Therefore, achieving the optimum solutions can reduced the systems cost and delay. On the other hand, Genetic algorithms (GAs) are powerful function optimizers that are used successfully to solve problems in many different disciplines. Parallel GAs (PGAs) are particularly easy to implement and promise substantial gains in performance and results. In this paper, we present a PGA-based approach to achieve near optimal solutions for HW/SW... 

The challenge of finding an optimized and reliable path dates back to emersion of mobile robots. Several approaches have been developed that have partially answered this need. Satisfying results in previous implementations has led to an increased utilization of sampling-based motion planning algorithms in recent years, especially in high degrees of freedom (DOF), fast evolving environments. Another advantage of these algorithms is their probabilistic completeness that guarantees delivery of a path in sufficient time, if one exists. On the other hand, sampling based motion planners leave no comment on safety of the planned path. This paper suggests biasing the Rapidly-exploring Random Trees... 

In this paper, the problem of scheduling commercial messages during the peak of viewing time of a TV channel is formulated as a combinatorial auction-based mathematical programming model. Through this model, a profitable and efficient mechanism for allocating the advertising time to advertisers is developed by which the revenue of TV channels is maximised while the effectiveness of advertising is increased. We developed a steady-state genetic algorithm to find an optimal or a near optimal solution for the proposed problem. A computational experiment was conducted for evaluating the efficiency of the proposed algorithm. A set of test problems with different sizes were generated, using the... 

We consider nonlinear optimization problems constrained by a system of fuzzy relation equations. The solution set of the fuzzy relation equations being nonconvex, in general, conventional nonlinear programming methods are not practical. Here, we propose a genetic algorithm with max-product composition to obtain a near optimal solution for convex or nonconvex solution set. Test problems are constructed to evaluate the performance of the proposed algorithm showing alternative solutions obtained by our proposed model  

New days, the concepts of 'Smart Grid' and 'Energy Hub' have been introduced to improve the operation of the energy systems. This paper introduces a new conception entitling Smart Energy Hub (S. E. Hub), as a multi-carrier energy system in a smart grid environment. To show the application of this novel idea, we present a residential S. E. Hub which employs Reinforcement Learning (RL) method for finding a near optimal solution. The simulation results show that by applying the S. E. Hub model and then using the proposed method for a residential customer, running cost is reduced substantially. While, comparing with the classical ones, the RL method does not require any data about the... 

In this paper a two level supply chain system is studied, in which the final demand is assumed to be fuzzy with triangular membership function. The inventory control policy of (r, Q) is followed for this system and unsatisfied demand is assumed to be back ordered. The objective is to minimize the total cost of the system, including ordering, holding and shortage costs. The model happens to be a nonlinear programming. Considering the complexity arising from the model, we also develop a genetic algorithm to obtain a near-optimal solution. The method is illustrated through some numerical examples  

Single-Row Facility Layout Problem (SRFLP) is a http://library.sharif.ir/web-manage/catalog/resource.do?method=edit&flowLastAction=view&id=447751special class of facilitylayout problems, consists of finding an optimal linear placement of rectangularfacilities with varying dimensions on a straight line. In this research, wefirst present a theorem to find the optimal solution of a special case of SRFLP.The results obtained by this theorem are very useful in reducing thecomputational efforts when, later on, a new algorithm based on tabu search ispresented for SRFLP. Computational results of the proposed algorithm onbenchmark problems show the efficiency of the algorithm compared to the... 

There is no method to determine the optimal topology for multi-layer neural networks for a given problem. Usually the designer selects a topology for the network and then trains it. Since determination of the optimal topology of neural networks belongs to class of NP-hard problems, most of the existing algorithms for determination of the topology are approximate. These algorithms could be classified into four main groups: pruning algorithms, constructive algorithms, hybrid algorithms and evolutionary algorithms. These algorithms can produce near optimal solutions. Most of these algorithms use hill-climbing method and may be stuck at local minima. In this article, we first introduce a... 

Motivated by the bus escape routing problem in printed circuit boards (PCBs), we study the following optimization problem: given a set of rectangles attached to the boundary of a rectangular region, find a subset of nonoverlapping rectangles with maximum total weight. We present an efficient algorithm that solves this problem optimally in O(n4) time, where n is the number of rectangles in the input instance. This improves over the best previous O(n6) -time algorithm available for the problem. We also present two efficient approximation algorithms for the problem that find near-optimal solutions with guaranteed approximation factors. The first algorithm finds a 2-approximate solution in O(n2)... 

Many companies regularly run Big Data analysis, and need to optimize their resource usage considering cost, deadline, and environmental impact simultaneously. The cloud allows choosing from various virtual machines (VM) where the number and type of VMs affect the outcome such as the time for data placement and data shuffle phases, a task's energy consumption and execution time, and the makespan of jobs. We provide provisioning and scheduling algorithms to minimize environmental impact, considering the above factors, for frequently executed MapReduce jobs. To mathematically model the problem and obtain the optimal solution, we present an Integer Linear Programming (ILP) model and then... 

Considering a multihop cellular system with one relay per sector, an effective modeling for the joint base-station/relay assignment, rate allocation, and routing scheme is proposed and formulated under a single problem for the downlink. This problem is then formulated as a multidimensional multichoice knapsack problem (MMKP) to maximize the total achieved throughput in the network. The well-known MMKP algorithm based on Lagrange multipliers is modified, which results in a near-optimal solution with a linear complexity. The notion of the infeasibility factor is also introduced to adjust the transmit power of base stations and relays adaptively. To reduce the complexity, and in order to... 

The advent of various real-time multimedia applications in high-speed networks creates a need for quality of service (QoS) based multicast routing. Two important QoS constraints are the bandwidth constraint and the end-to-end delay constraint. The QoS based multicast routing problem is a known NP-complete problem that depends on (1) bounded end-to-end delay and link bandwidth along the paths from the source to each destination, and (2) minimum cost of the multicast tree. In this paper we describe a new representation, called node parent index (NPI) representation, for representing trees and describe harmony operations accord to this representation. The presented algorithm is based on the...