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حرية الوصول المقاله
1 - بررسی روش‌های فراابتکاری برای مسائل بهینه‌سازی
مهدی فضلیدر این مقاله به بررسی مشکلات مربوط به مسیریابی و موقعیت یابی با متغیرهای واقعی و بررسی سوالات مربوطه می پردازیم. این تصمیمات مهندسی، موجودی و بهینه سازی در یک سیستم زنجیره تامین چندلایه شامل تامین کنندگان، انبارها و خریداران مختلف گرفته می شود. ما به دنبال راه های جدیدی أکثردر این مقاله به بررسی مشکلات مربوط به مسیریابی و موقعیت یابی با متغیرهای واقعی و بررسی سوالات مربوطه می پردازیم. این تصمیمات مهندسی، موجودی و بهینه سازی در یک سیستم زنجیره تامین چندلایه شامل تامین کنندگان، انبارها و خریداران مختلف گرفته می شود. ما به دنبال راه های جدیدی برای مدیریت مکان و مسیریابی کارآمد و موثر هستیم. به منظور افزایش کارایی و دستیابی به نتایج بهینه، از روش های اکتشافی و فراابتکاری استفاده شده است. در تکنیک های فراابتکاری، معمولا از تکنیک ترکیبی برای افزایش عملکرد استفاده می شود. بنابراین، این مقاله مروری به بررسی روش‌های فراابتکاری و تحلیل مشکلات مکان با استفاده از کمیت‌های مختلف می‌پردازد. همچنین مزایا و معایب هر روش را برای حل بهینه این مشکلات بررسی می کند تا روش های کاربردی و کارآمد را معرفی کند. تفاصيل المقالة -
حرية الوصول المقاله
2 - مقایسه شبکه عصبی، سیستم فازی عصبی و مدل AR در پیش-بینی بازده اوراق بهادار و الگوریتم جستجوی موجودات همزیست با ممتیک آن در بهینه سازی پرتفوی
سیدمهدی رضایی محمود باغجری پوریا مظاهری فردر این مطالعه، به بررسی و مقایسه عملکرد الگوریتم جستجوی موجودات همزیست و ممتیک جستجوی موجودات همزیست در بدست آوردن مرزکارا مدل میانگین نیم واریانس مقید پرداخته می شود. و همچنین سه روش AR خطی شبکه عصبی و سیستم فازی عصبی در بدست آوردن بازده مورد انتظار، مورد مقایسه قرار أکثردر این مطالعه، به بررسی و مقایسه عملکرد الگوریتم جستجوی موجودات همزیست و ممتیک جستجوی موجودات همزیست در بدست آوردن مرزکارا مدل میانگین نیم واریانس مقید پرداخته می شود. و همچنین سه روش AR خطی شبکه عصبی و سیستم فازی عصبی در بدست آوردن بازده مورد انتظار، مورد مقایسه قرار می گیرند. در این مطالعه از 23 سهم فعال تر بازار استفاده می شود که بازده آنها از تاریخ 01/04/93 تا 01/12/95 مورد استفاده قرار گرفته است. نتایج نشان می دهد که الگوریتم ممتیک جستجوی موجودات همزیست برخلاف استفاده از زمان بیشتر، توانسته عملکرد بهتری را به نمایش بگذارد و همچنین، مقایسه روش های پیش بینی بازده مورد انتظار نشان می دهد که سیستم فازی عصبی توانسته با خطای کمتری بازده مورد انتظار را پیش بینی نماید. در نهایت، با مقایسه مرزکارای پیش بینی شده و مرزکارای واقعی، به این نتیجه می رسیم که مدل پیش بینی مورد نظر در ریسک های کمتر پیش بینی بهتری انجام داده است که در آن ناحیه می توان با اطمینان بیشتری نسبت به تخصیص دارایی ها اقدام نمود. تفاصيل المقالة -
حرية الوصول المقاله
3 - The Effects of Technical and Organizational Activities on Redundancy Allocation Problem with Choice of Selecting Redundancy Strategies Using the memetic algorithm
M. Sharifi MR. Shahriari A. ZaretalabRedundancy allocation problem is one of most important problems in reliability area. This problem involves with the suitable redundancy levels under certain strategies to maximizing system reliability under some constraints. Many changes have been made on this problem t أکثرRedundancy allocation problem is one of most important problems in reliability area. This problem involves with the suitable redundancy levels under certain strategies to maximizing system reliability under some constraints. Many changes have been made on this problem to draw the problem near to real situations. Selecting the redundancy strategy, using different system configuration are some of these changes. In this paper we considered the effects of technical and organizational activities on this problem and showed the difference between the system reliability with and without using these activities. In this paper we worked on a system containing s sub-systems connected serially together. Each sub-system contains parallel components that can be selected from different component types and all of each sub-system components must be the same. Because redundancy allocation problem belongs to Np. Hard problems, we used a new meta-heuristic algorithm called memetic competition algorithm for solving the presented problem and compared the result of this algorithm and other solving methods. تفاصيل المقالة -
حرية الوصول المقاله
4 - Distributed Routing Protocol in Wireless Sensor Networks through Mimetic Algorithm and Time-Sharing Approach to Select Cluster Head
Sahar Nassirpour Shayesteh TabatabaeiWireless sensor networks include sensor nodes communicating each other through wireless links for effective data collection and routing. These wireless nodes are of limited processing power, memory, communication range, channel band width, and battery capacity, from amo أکثرWireless sensor networks include sensor nodes communicating each other through wireless links for effective data collection and routing. These wireless nodes are of limited processing power, memory, communication range, channel band width, and battery capacity, from among which the most important is limited capacity of batteries which are unchangeable, under many conditions. The limitation encourages designing efficient protocols in terms of energy consumption. Using clustering is one of the methods to optimize energy consumption. On the other hand, a technical challenge in successful expansion of wireless sensor networks and their exploitation is effective usage made of limited channel band width. To overcome the challenge, one of the methods is dividing schedule of channel usage through TDMA method (Time-Division Multiple Access) so that each cluster head node creates a schedule for transmission of data from member nodes of the cluster through TDMA. Accordingly, in the paper, a distributed routing protocol based on clustering through usage of mimetic algorithm and time-sharing approach is proposed; and, it is capable of optimizing energy consumption and throughput rate, as well as reducing delay. The simulation results are indicative of better performance of proposed method, compared to IEEE 802.15.4 Standard. تفاصيل المقالة -
حرية الوصول المقاله
5 - MMDT: Multi-Objective Memetic Rule Learning from Decision Tree
Bahareh Shaabani Hedieh SajediIn this article, a Multi-Objective Memetic Algorithm (MA) for rule learning is proposed. Prediction accuracy and interpretation are two measures that conflict with each other. In this approach, we consider accuracy and interpretation of rules sets. Additionally, individ أکثرIn this article, a Multi-Objective Memetic Algorithm (MA) for rule learning is proposed. Prediction accuracy and interpretation are two measures that conflict with each other. In this approach, we consider accuracy and interpretation of rules sets. Additionally, individual classifiers face other problems such as huge sizes, high dimensionality and imbalance classes’ distribution data sets. This article proposed a way to handle imbalance classes’ distribution. We introduce Multi-Objective Memetic Rule Learning from Decision Tree (MMDT). This approach partially solves the problem of class imbalance. Moreover, a MA is proposed for refining rule extracted by decision tree. In this algorithm, a Particle Swarm Optimization (PSO) is used in MA. In refinement step, the aim is to increase the accuracy and ability to interpret. MMDT has been compared with PART, C4.5 and DTGA on numbers of data sets from UCI based on accuracy and interpretation measures. Results show MMDT offers improvement in many cases. تفاصيل المقالة -
حرية الوصول المقاله
6 - A Memetic Algorithm for Hybrid Flowshops with Flexible MachineAvailability Constraints
Fariborz Jolai mostafa zandieh Bahman NaderiThis paper considers the problem of scheduling hybrid flowshops with machine availability constraints (MAC) to minimize makespan. The paper deals with a specific case of MAC caused by preventive maintenance (PM) operations. Contrary to previous papers considering fixed أکثرThis paper considers the problem of scheduling hybrid flowshops with machine availability constraints (MAC) to minimize makespan. The paper deals with a specific case of MAC caused by preventive maintenance (PM) operations. Contrary to previous papers considering fixed or/and conservative policies, we explore a case in which PM activities might be postponed or expedited while necessary. Regarding this flexibility in PM activities, we expect to obtain more efficient schedule. A simple technique is employed to schedule production jobs along with the flexible MACs caused by PM. To solve the problem, we present a high performing metaheuristic based on memetic algorithm incorporating some advanced features. To evaluate the proposed algorithm, the paper compares the proposed algorithm with several wellknown algorithms taken from the literature. Finally, we conclude that the proposed algorithm outperforms other algorithms. تفاصيل المقالة -
حرية الوصول المقاله
7 - A Review of Meta-heuristics Algorithms for Solving Fuzzy Location Routing Problems
Mehdi Fazli Somayyeh Faraji AmooginIn this paper, we consider the issues related to multi-periodic and multi-period routing and positioning, and investigate the relevant constraints. Those decisions on location allocation, inventory and routing are made in a three-tiered supply chain, including suppliers أکثرIn this paper, we consider the issues related to multi-periodic and multi-period routing and positioning, and investigate the relevant constraints. Those decisions on location allocation, inventory and routing are made in a three-tiered supply chain, including suppliers, warehouses and customers. We seek new ways to decide on location and routing simultaneously and efficiently. To maximize the search space and to achieve optimum results, heuristic and meta-heuristic methods have been used. The meta-heuristics technique is usually used to increase the performance of the combination technique. Therefore, this article provides an overview of meta-heuristic methods and their combinations to solve problems. It also examines the advantages and disadvantages of the proposed methods to solve these problems in order to provide more efficient methods. تفاصيل المقالة -
حرية الوصول المقاله
8 - A new memetic algorithm for mitigating tandem automated guided vehicle system partitioning problem
Parinaz PourrahimianAutomated Guided Vehicle System (AGVS) provides the flexibility and automation demanded by Flexible Manufacturing System (FMS). However, with the growing concern on responsible management of resource use, it is crucial to manage these vehicles in an efficient way in ord أکثرAutomated Guided Vehicle System (AGVS) provides the flexibility and automation demanded by Flexible Manufacturing System (FMS). However, with the growing concern on responsible management of resource use, it is crucial to manage these vehicles in an efficient way in order reduces travel time and controls conflicts and congestions. This paper presents the development process of a new Memetic Algorithm (MA) for optimizing partitioning problem of tandem AGVS. MAs employ a Genetic Algorithm (GA), as a global search, and apply a local search to bring the solutions to a local optimum point. A new Tabu Search (TS) has been developed and combined with a GA to refine the newly generated individuals by GA. The aim of the proposed algorithm is to minimize the maximum workload of the system. After all, the performance of the proposed algorithm is evaluated using Matlab. This study also compared the objective function of the proposed MA with GA. The results showed that the TS, as a local search, significantly improves the objective function of the GA for different system sizes with large and small numbers of zone by 1.26 in average. تفاصيل المقالة -
حرية الوصول المقاله
9 - A redundancy allocation problem with the choice of redundancy strategies by a memetic algorithm
J Safari R Tavakkoli-MoghaddamThis paper proposes an efficient algorithm based on memetic algorithm (MA) for a redundancy allocation problem without component mixing (RAPCM) in a series-parallel system when the redundancy strategy can be chosen for individual subsystems. Majority of the solution met أکثرThis paper proposes an efficient algorithm based on memetic algorithm (MA) for a redundancy allocation problem without component mixing (RAPCM) in a series-parallel system when the redundancy strategy can be chosen for individual subsystems. Majority of the solution methods for the general RAPCM assume that the type of a redundancy strategy for each subsystem is pre-determined and known a priori. In general, active redundancy has traditionally received greater attention; however, in practice both active and cold-standby redundancies may be used within a particular system design. The choice of the redundancy strategy then becomes an additional decision variable. Thus, the problem is to select the best redundancy strategy, component and redundancy level for each subsystem in order to maximize the system reliability under system-level constraints. Due to its complexity and NP-hardness, it is so difficult to optimally solve such a problem by using traditional optimization tools. To validate the performance of the proposed MA in terms of solution quality, a number of test problems are examined and the robustness of this algorithm is then discussed. Finally, the related results are reported and it is shown that the proposed MA performs well. تفاصيل المقالة -
حرية الوصول المقاله
10 - SOLVING A STEP FIXED CHARGE TRANSPORTATION PROBLEM BY A SPANNING TREE-BASED MEMETIC ALGORITHM
Saber Molla-Alizadeh-Zavardehi Masoud Sanei Reza Soltani Ali MahmoodiradIn this paper, we consider the step fixed-charge transportation problem (FCTP) in which a step fixed cost, sometimes called a setup cost, is incurred if another related variable assumes a nonzero value. In order to solve the problem, two metaheuristic, a spanning tree-b أکثرIn this paper, we consider the step fixed-charge transportation problem (FCTP) in which a step fixed cost, sometimes called a setup cost, is incurred if another related variable assumes a nonzero value. In order to solve the problem, two metaheuristic, a spanning tree-based genetic algorithm (GA) and a spanning tree-based memetic algorithm (MA), are developed for this NP-hard problem. For comparing GA and MA, twenty eight problems with different specifics have been generated at random and then the quality of the proposed algorithms was evaluated using the relative percentage deviation (RPD) method. Finally, based on RPD method, we investigate the impact of increasing the problem size on the performance of our proposed algorithms. تفاصيل المقالة
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