Reliable Network Design for Ethernet Ring Mesh Networks

The aim of this paper is to propose a robust reliable bi-objective supply chain network design (SCND) model that is capable of controlling different kinds of uncertainties, concurrently. In this regard, stochastic bi-level scenario based programming approach which is used to model various scenarios related to strike of disruptions. The well-known method helps to overcome adverse effects of disruptions and extend a network that is less vulnerable regarding disruptions strike. Also, scenario-based modeling approach enables decision makers (DMs) to the model uncertainty of model parameters regarding different scenarios that are disregarded in reliable SCND research scope. An effective robust programming method is employed to control the risk-aversion level of output decisions that helps company managers to adjust long-term effects of their decisions via determining uncertainty level of model parameters. Notably, extended bi-objective programming model minimizes total costs of network design aside with maximization of responsiveness of supply chain network. Agile and fast performing networks could be regarded as a long-term competitive advantage for companies that are modeled in the extended form as a different objective besides cost minimization. Finally, the extended robust reliable network model is implemented and evaluated based on real case study of a national project and output results demonstrates efficiency and applicability of proposed reliable network.

A heuristic algorithm for optimal cost design of gravity-fed water distribution networks. a real case study

Synthesis and methodology for optimal design of a parallel remote center of motion mechanism: Application to robotic eye surgery

Modeling and design of global logistics systems: A review of integrated strategic and tactical models and design algorithms

Transportation network design for maximizing flow-based accessibility

In this paper, we have considered an optimal design and provisioning of WDM networks for the grooming of sub-wavelengths traffic requests. As higher layer electronic ports, such as transceivers and optical splitters are dominant cost factors of an optical network, it is essential to reduce their numbers of use while grooming the multicast traffic requests into high bandwidth light-trees. This paper provides an optimal cost design of WDM networks with multicast traffic grooming under static traffic demand. We develop a unified framework for the optimal provisioning of different practical scenarios of multicast traffic grooming in a static traffic scenario. In this study, we design an Integer linear Programming (ILP) formulation for multicast traffic grooming to minimize the cost associated with the higher layer electronic ports such as transceivers, splitters and wavelengths, and simultaneously maximize the bandwidth utilization of the network. We propose a heuristic algorithm called Efficient Light-Tree based Multicast Traffic Grooming (ELT-MTG) algorithm to achieve scalability in large size optical networks. Simulations are conducted on several standard well-known WDM mesh networks to study the design cost (based on number of transceivers, optical splitters and wavelengths) used in the networks. The result, thus obtained by comparison, helped us to conclude that the proposed approach ELT-MTG gives better performance than well-known existing logical-first sequential routing with single-hop grooming (LFSEQSH) and logical-first sequential routing with multi-hop grooming (LFSEQMH) algorithms in a static traffic environment.

Many network-reliability analysis techniques define and compute a variety of reliability measures. Most techniques assume that network connectivity is the only determining factor in network reliability; and merely analyze an existing network structure but do not provide any methodology for reliable design. This paper presents a heuristic design algorithm to enhance the reliability of existing communication networks by modifying their topology. This algorithm improves the reliability of the least reliable node (reliability is the probability that messages transmitted from a given node reach their destination). To use this algorithm on large networks, a reliability analysis method is developed which determines approximate network reliability values in linear-time when an upper bound is placed upon the in-degree of all network nodes. The heuristic network design algorithm uses this approximate reliability analysis technique to place additional links. The goal of this link placement is to improve the reliability of the least-reliable node. The placement of additional links is a function of both the traffic distribution and the connectivity of the network. This process continues until either a desired level of network reliability is achieved or a maximum number of additional links has been added. A unique feature of this design strategy is that it has quadratic time-complexity when the maximum in-degree of all network nodes is limited. >

(Keywords) combinatorial optimization problem, rational construction, simulated annealing, agricultural facility, optimal layout design Abstract In this study, optimal layout design approach was used to solve problems related to site layout design of agricultural facilities such as refrigeration house, grading and packing house and warehouse. A basic program to support the rational construction of such facilities using Simulated Annealing (SA), one heuristic algorithm and one solution for combinatorial optimization problems, was coded in C language (Satake(1999)). Layout design simulations were carried out to obtain information for the development of a program for solving practical problems. And, to clarify the feasibility of applying SA to the optimal layout design problems, the layout design simulation using the hill climbing (HC), which is another heuristic algorithm, was carried out for comparison with SA. As a result of the comparison with the optimum solution by HC, the value of cost evaluation by SA using exponential annealing was lower than that of hill climbing. Furthermore, in addition to this simulation, preliminary layout design simulation was also carried out to determine the applicability of the optimal layout design simulator to practical design. In this study, the layout design for a new building and parking was carried out. In the layout design, the site is not rectangular. As a result, the optimal design satisfying our condition was obtained.

Multi-objective green scheduling of integrated flexible job shop and automated guided vehicles

Hardware/software (HW/SW) partitioning and scheduling are the crucial steps during HW/SW co-design. It has been shown that they are classical combinatorial optimization problems. Due to the possible sequential or concurrent execution of the tasks, HW/SW partitioning and scheduling has become more difficult to solve optimally. In this paper more efficient heuristic algorithms are proposed for the HW/SW partitioning and scheduling. The proposed algorithm partitions a task graph by iteratively moving the task with highest benefit-to-area ratio in higher priority. The benefit-to-area ratio is updated in each iteration step to cater for the task concurrence. The proposed algorithm for task scheduling executes the task lying in hardware-only critical path in higher priority to enhance the task forecast. A large body of experimental results conclusively shows that the proposed heuristic algorithm for partitioning is superior to the latest efficient combinatorial algorithm (Tabu search) cited in this paper. Moreover, the Tabu search for partitioning has been further improved by utilizing the proposed heuristic solution as its initial solution. In addition, the proposed scheduling algorithm obtains the improvements over the most widely used approaches by up to 10% without large increase in running time.

We discuss how the idea of unicast 1+1 protection can be efficiently extended to protect multicast connections in optical backbone networks. Particularly, we show how to achieve instantaneous failure recovery and cost efficiency by allowing intermediate nodes to merge their incoming flows by a simple network code, i.e., logical OR operation. Under simple network coding, the problem of minimum cost multicast 1+1 protection is formulated as a 2-connectivity problem. In order to solve this problem, an optimal ILP and three efficient heuristic algorithms are proposed. Simulation results on real-world networks show that the average cost of our best heuristic algorithm is only 2.6 % higher compared to the optimal ILP solution.

Automatic layout of tables is required in online applications because of the need to tailor the layout to the viewport width, choice of font, and dynamic content. However, if the table contains text, minimizing the height of the table for a fixed maximum width is NP-hard. Thus, more efficient heuristic algorithms are required. We evaluate the HTML table layout recommendation and find that while it generally produces quite compact layout it is brittle and can lead to quite uncompact layout. We present an alternate heuristic algorithm. It uses a greedy strategy that starts from the widest reasonable layout and repeatedly chooses to narrow the column for which narrowing leads to the least increase in table height. The algorithm is simple, fast enough to be used in online applications, and gives significantly more compact layout than is obtained with HTML’s recommended table layout algorithm.

This paper describes the two-stage flowshop problem when there are identical multiple machines at each stage, and shows that the problem is NP-complete. An efficient heuristic algorithm is developed for finding an approximate solution of a special case when there is only one machine at stage 2. The effectiveness of the proposed heuristic algorithm in finding a minimum makespan schedule is empirically evaluated and found to increase with the increase in the number of jobs.

Scheduling of meetings is one of the basic functions demanded in office automation. With respect to the automation of this function, the Meeting Timetable Rearrangement problem (MTR) to update a current meeting timetable for an additional meeting has been formulated. However, it has already been shown that MTR is NP‐hard. Consequently, we should develop an approximation algorithm or a heuristic algorithm for MTR. Such an algorithm is required to find a feasible solution which satisfies all constraints, but not necessarily an optimal solution. This paper discusses a problem to determine whether or not there exists a feasible solution for a given instance of MTR. First, we show that this problem is NP‐complete. That is, there is no polynomial‐time approximation algorithm for MTR unless P = NP. This implies that we should develop a heuristic algorithm for MTR. Second, we present a polynomial‐time algorithm which finds a feasible solution for a subproblem of MTR. By combining this algorithm and a hill‐climbing approach, an efficient heuristic algorithm can be developed.

Both network function virtualization (NFV) and edge computing (EC), especially the latter, are attracting more and more attention in recent years. A growing number of network service providers are migrating their services from the cloud to the edge for better QoS services, while the recent researches on NFV also concentrate on deploying NFV services in edge computing networks. However, NFV deployment in edge networks is a troublesome challenge and is fairly alien from conventional NFV deployment problems in data centres. Edge network differs from the data center network in the following two aspects: firstly, edge nodes are constrained in computing capacity, and secondly, the network connections between edge nodes are unstable and dynamic, which may show large variance over time. This means edge computing should be designed for high-efficient use of physical edge nodes’ resources. To address the challenges above, we investigate a new NFV Service Chain Placement problem in edge computing environments (NSCP-EC) in this paper. We first prove that the NSCP-EC problem is NP-complete. Then we propose a new metric which can better measure the capacity utilization rate of physical resources, and analyze its advantages with details. Based on the new metric, we propose two heuristic but efficient algorithms called MINI and MINI-tree. To confirm the performance of the two algorithms, we conduct simulations. The result demonstrates that MINI gains an advantage over genetic algorithm (GA) and MINI-tree orevails over MINI in tree topology conditions in the aspects of physical resource utilization, acceptance rate and running time. Both theoretical analysis and simulation results confirm the feasibility of the algorithms.