Sharif Digital Repository

Abstract: Advancements in microscale technologies have prompted a demand for high precision micro-manipulation. Microgrippers are the primary means of conducting micro-scale operations, and they significantly affect the procedure's performance. This paper presents a novel optimized design for compliant microgrippers, intending to enhance functionality and durability. The mainframe of the proposed microgripper is based on a compact flexure-based compliant structure with four stages of movement amplification. Experiments were designed based on the L25 Taguchi orthogonal arrays. The experiments were conducted using the finite element method in Abaqus 6.14 workbench. Range of motion and maximum... 

Efficient management of supply chain (SC) requires systematic considerations of miscellaneous issues in its comprehensive version. In this paper, a multi-periodic structure is developed for a supply chain network design (SCND) involving suppliers, factories, distribution centers (DCs), and retailers. The nature of the logistic decisions is tactical that encompasses procurement of raw materials from suppliers, production of finished product at factories, distribution of finished product to retailers via DCs, and the storage of raw materials and end product at factories and DCs. Besides, to make the structure more comprehensive, a flow-shop scheduling model in manufacturing part of the SC is... 

In market-based planning studies, the financial aspects of transmission grids have been posed as a major challenge since these are important keys to provide a non-discriminative and competitive environment for energy market participants. In this respect, this paper proposes a probabilistic multi-objective transmission expansion planning algorithm considering private investors' preferences, technical concerns, and random nature of power system uncertainties. The combination of Non-Dominated Sorting Genetic Algorithm II, as a widely-used robust multi-objective optimization technique, and point estimation method is employed to handle non-commensurable probabilistic objective functions. The IEEE... 

In this study, a bi-objective multi-state redundancy allocation problem of series-parallel systems consisting of some serial subsystems, each with non-repairable components in parallel, is investigated. Furthermore, due to uncertainty involved, both the performance rates and the availabilities of components are considered fuzzy. In addition, two strategies of all-unit and incremental-quantity discounts are used to purchase the components and that the fuzzy universal generating function (FUGF) is employed to evaluate the system availability. The aim is to find the optimal redundancy so as within limited budget and system weight the maximum system availability is obtained while the total cost... 

Most of the reported robust and non-robust optimization works are formulated based on a single-objective optimization, commonly in terms of net present value. However, variation of economical parameters such as oil price and costs forces such high computational optimization works to regenerate their optimum water injection policies. Furthermore, dynamic optimization strategies of water-flooding often lack robustness to geological uncertainties. This paper presents a multi-objective while robust optimization methodology by incorporating three dedicated objective functions. The goal is to determine optimized and robust water injection policies for all injection wells. It focuses on reducing... 

The increasing use of electrical energy in nowadays modern societies and industries has brought about a sharp need for more efficient means of electricity generation. It seems rather logical to increase the electricity production proportional to the increasing rate of the demand. Distributed Generation (DG) has been recently accepted to be one of the most efficient means of electricity generation, particularly near to the load centers. The DG has been also considered in the generation expansion planning of power systems. In this paper, three main factors associated with the DGs placement procedure is scrutinized through a multi-objective optimization approach. One of the main factors... 

Bi-objective optimization of a multi-product multi-period three-echelon supply-chain-network problem is aimed in this paper. The network consists of manufacturing plants, distribution centers (DCs), and customer nodes. To bring the problem closer to reality, the majority of the parameters in this network including fixed and variable costs, customer demand, available production time, set-up and production times, all are considered stochastic. The goal is to determine the quantities of the products produced by the manufacturing plants in different periods, the number and locations of the warehouses, the quantities of products transported between the supply chain entities, the inventory of... 

In this study, a bi-objective multi-state redundancy allocation problem of series-parallel systems consisting of some serial subsystems, each with non-repairable components in parallel, is investigated. Furthermore, due to uncertainty involved, both the performance rates and the availabilities of components are considered fuzzy. In addition, two strategies of all-unit and incremental-quantity discounts are used to purchase the components and that the fuzzy universal generating function (FUGF) is employed to evaluate the system availability. The aim is to find the optimal redundancy so as within limited budget and system weight the maximum system availability is obtained while the total cost... 

Redundancy Allocation Problem (RAP) is one way to increase system reliability. In most of the models developed so far for the RAP, system components are considered to have a binary state consisting of "working perfect" or "completely failed". However, to suit the real-world applications, this assumption has been relaxed in this paper, such that components can have three states. Moreover, a Bi-Objective RAP (BORAP) is modeled for a system with serial subsystems, in which non-repairable tri-state components of each subsystem are configured in parallel and the subsystem works under k-out-of-n policy. Furthermore, to enhance system reliability, technical and organizational activities that can... 

The facility location problem and its related financial issues have a significant impact on the configuration of a supply chain structure (SCS). Although affording the setup cost of facilities requires a huge financial investment, a meticulous planning to recoup it has been neglected by an overwhelming majority of previous studies. To fill this gap, an economical investment plan of facilities is determined by striking a trade-off between the contribution of the stockholders’ capital and the loan arrangement. In the context of a multiperiod three-echelon SCS, the model also determines the optimum location of plants and the best supply and distribution patterns. The model maximizes the fill... 

This study addresses a many-to-many hub location-routing problem where the best-found locations of hubs and the best-found tours for each hub are determined with simultaneous pickup and delivery within the hard time window. To find practical solutions, the hubs and transportation fleet have constrained capacity, in which every node can be serviced by multiple allocations with the hard time window and limited tour length. First, a bi-objective optimization model is proposed to balance travel costs among different routes and to minimize the total sum of fixed costs of locating hubs, the costs of handling, traveling, assigning, and transportation costs. The problem is then solved using an... 

Robust optimization (RO) approach is inherently a multi-objective paradigm. The proposed multi-objective optimization formulation would attempt to find the optimum - yet robust - water injection policies. Two multi-objective, Pareto-based robust optimization scenarios have been investigated to encounter the permeability uncertainties. These multi-objective RO scenarios have been done based on a small representative set of realizations but they have introduced optimum points that could be reliable for the original set of realizations either. In both scenarios, the desired objective functions are expected value and variance of Net Present Value (NPV). The underlying RO scenarios have been done... 

In this paper, optimal trajectories of a spacecraft traveling from Earth to Moon using impulsive maneuvers (ΔV maneuvers) are investigated. The total flight time and the summation of impulsive maneuvers ΔV are the objective functions to be minimized. The main celestial bodies influencing the motion of the spacecraft in this journey are Sun, Earth and Moon. Therefore, a three-dimensional restricted four-body problem (R4BP) model is utilized to represent the motion of the spacecraft in the gravitational field of these celestial bodies. The total ΔV of the maneuvers is minimized by eliminating the ΔV required for capturing the spacecraft by Moon. In this regard, only a mid-course impulsive... 

A novel bi-objective three-echelon supply chain problem is formulated in this paper in which cross-dock facilities to transport the products are modeled as an M/M/m queuing system. The proposed model is validated using the epsilon constraint method when applied to solve some small-size problems. Since the problem belongs to the class of NP-hard and that it is of a bi-objective type, a multi-objective particle swarm optimization (MOPSO) algorithm with a new solution structure that satisfies all of the constraints is developed to find Pareto solutions. As there is no benchmark available in literature, three other multi-objective meta-heuristic algorithms called non-dominated ranking genetic... 

The current study aims to simultaneously and comprehensively investigate the performance of four types of recuperative heat exchangers applied in 200 kW microturbines by using numerical method. Different fin configurations including rectangular, triangular, louver and offset strip fins are employed in the recuperators to enhance the heat transfer rate. Additionally, the calculations are separately undertaken for both counter and cross-flow arrangements. To achieve the best performance, a three-objective optimization problem is solved using Non-dominated Sorting Genetic Algorithm (NSGA-II). Recuperator effectiveness and exergy efficiency and total cost are considered as the objective... 

Diabetes mellitus is a medical condition examined by data miners for reasons such as significant health complications in affected people, the economic impact on healthcare networks, and so on. In order to find the main causes of this disease, researchers look into the patient's lifestyle, hereditary information, etc. The goal of data mining in this context is to find patterns that make early detection of the disease and proper treatment easier. Due to the high volume of data involved in therapeutic contexts and disease diagnosis, provision of the intended treatment method become almost impossible over a short period of time. This justifies the use of pre-processing techniques and data...