Solving material distribution routing problem in mixed manufacturing systems with a hybrid multi-objective evolutionary algorithm

The material distribution routing problem in the manufacturing system is a complex combinatorial optimization problem and its main task is to deliver materials to the working stations with low cost and high efficiency. A multi-objective model was presented for the material distribution routing problem in mixed manufacturing systems, and it was solved by a hybrid multi-objective evolutionary algorithm (HMOEA). The characteristics of the HMOEA are as follows: 1) A route pool is employed to preserve the best routes for the population initiation; 2) A specialized best?worst route crossover (BWRC) mode is designed to perform the crossover operators for selecting the best route from Chromosomes 1 to exchange with the worst one in Chromosomes 2, so that the better genes are inherited to the offspring; 3) A route swap mode is used to perform the mutation for improving the convergence speed and preserving the better gene; 4) Local heuristics search methods are applied in this algorithm. Computational study of a practical case shows that the proposed algorithm can decrease the total travel distance by 51.66%, enhance the average vehicle load rate by 37.85%, cut down 15 routes and reduce a deliver vehicle. The convergence speed of HMOEA is faster than that of famous NSGA-II.

A distributed on-demand bandwidth-constrained multicast routing protocol for wireless ad hoc networks

To meet the bandwidth requirement for the multicasting data flow in ad hoc networks, a distributed on- demand bandwidth-constrained multicast routing （BCMR） protocol for wireless ad hoc networks is proposed. With this protocol, the resource reservation table of each node will record the bandwidth requirements of data flows, which access itself, its neighbor nodes and hidden nodes, and every node calculates the remaining available bandwidth by deducting the bandwidth reserved in the resource reservation table from the total available bandwidth of the node. Moreover, the BCMR searches in a distributed manner for the paths with the shortest delay conditioned by the bandwidth constraint. Simulation results demonstrate the good performance of BCMR in terms of packet delivery reliability and the delay. BCMR can meet the requirements of real time communication and can be used in the multicast applications with low mobility in wireless ad hoc networks.

Novel optimized routing algorithm for LEO satellite IP networks

A lot of routing algorithms have been proposed for low earth orbit（LEO） satellite IP networks in recent years,but most of them cannot achieve global optimization.The dynamic characters of LEO satellite networks are reflected in two aspects：topology and traffic change.The algorithms mentioned above are ＂hard routing＂ which only realize local optimization.A distributed soft routing algorithm combined with multi-agent system（MASSR） is proposed.In MASSR,mobile agents are used to gather routing information actively,and blackboard is introduced to achieve direct information exchange between agents.MASSR provides traffic adaptive routing and tracks the change of LEO satellite network topology.The performance of ant colony optimization（ACO） and MASSR are compared in Iridium constellation,and MASSR presents better end-to-end delay as well as enhanced robustness.

Inter-domain routing and wavelength assignment based on source routing in ASON

The inter-domain and intra-domain routings are treated jointly with dynamically distributed algorithms in automatically switched optical networks （ASON） based on source routing. The proposed algorithms are discussed through numerical calculations. The routing loops can be avoided efficiently and the inter-domain signaling complexity is reduced significantly. The performance of the blocking probability is also improved.

A Cloud Computing Perspective for Distributed Routing in Vehicular Environments

Vehicular networks have been envisioned to provide us with numerous interesting services such as dissemination of real-time safety warnings and commercial advertisements via car-to-car communication. However, efficient routing is a research challenge due to the highly dynamic nature of these networks. Nevertheless, the availability of connections imposes additional constraint. Our earlier works in the area of efficient dissemination integrates the advantages of middleware operations with muhicast routing to de- sign a framework for distributed routing in vehicular networks. Cloud computing makes use of pools of physical computing resourc- es to meet the requirements of such highly dynamic networks. The proposed solution in this paper applies the principles of cloud computing to our existing framework. The routing protocol works at the network layer for the formation of clouds in specific geo- graphic regions. Simulation results present the effieiency of the model in terms of serviee discovery, download time and the queu- ing delay at the controller nodes.

Distributed QoS-aware source-specific multicast routing protocol

A distributed QoS (quality of service) -aware source-specific multicast routing protocol—DQSSMR is proposed to increase the successful join ratio and lower the overhead of the control message in QoS required multicast routing. By an improved searching strategy, the cost of message control is reduced and the successful join ratio is increased. The network load is balanced due to the distributed routing operation and the scalability is enhanced further because of the usage of SSM (source- specific multicast) service model in DQSSMR. The analysis results indicate that DQSSMR performs as expected.

Bibliometric analysis and system review of vehicle routing optimization for emergency material distribution

Determining the optimal vehicle routing of emergency material distribution(VREMD)is one of the core issues of emergency management,which is strategically important to improve the effectiveness of emergency response and thus reduce the negative impact of large-scale emergency events.To summarize the latest research progress,we collected 511VREMD-related articles published from 2010 to the present from the Scopus database and conducted a bibliometric analysis using VOSviewer software.Subsequently,we cautiously selected 49 articles from these publications for system review;sorted out the latest research progress in model construction and solution algorithms;and summarized the evolution trend of keywords,research gaps,and future works.The results show that domestic scholars and research organizations held an unqualified advantage regarding the number of published papers.However,these organizations with the most publications performed poorly regarding the number of literature citations.China and the US have contributed the vast majority of the literature,and there are close collaborations between researchers from both countries.The optimization model of VREMD can be divided into single-,multi-,and joint-objective models.The shortest travel time is the most common optimization objective in the single-objective optimization model.Several scholars focus on multiobjective optimization models to consider conflicting objectives simultaneously.In recent literature,scholars have focused on the impact of uncertainty and special events(e.g.,COVID-19)on VREMD.Moreover,some scholars focus on joint optimization models to optimize vehicle routes and central locations(or material allocation)simultaneously.Solution algorithms can be divided into two primary categories,i.e.,mathematical planning methods and intelligent evolutionary algorithms.The branch and bound algorithm is the most dominant mathematical planning algorithm,while genetic algorithms and their enhancements are the most commonly used intelligent evolutionary algorithms.It is shown that the nondominated sorting genetic algorithmⅡ(NSGA-Ⅱ)can effectively solve the multiobjective model of VREMD.To further improve the algorithm’s performance,researchers have proposed improved hybrid intelligent algorithms that combine the advantages of NSGA-Ⅱand certain other algorithms.Scholars have also proposed a series of optimization algorithms for specific scenarios.With the development of new technologies and computation methods,it will be exciting to construct optimization models that consider uncertainty,heterogeneity,and temporality for large-scale real-world issues and develop generalized solution approaches rather than those applicable to specific scenarios.

Study on Optimal Topology for Computer Local Double Loop Networks

A dist ributed optimal local double loop (DOLDL) network is presented. Emphasis is laid on the topology and distributed routing algorithms for the DOLDL. On the basis of building an abstract model, a set of definitions and theorems are described and proved. An algorithm which can optimize the double loop networks is presented. The optimal values of the topologic parameters for the DOLDL have been obtained by the algorithm, and these numerical results are analyzed. The study shows that the bounds of the optimal diameter d and average hop distance a for this class of networks are [3N- 2]≤d≤[3N ] and (5N/9 (N-1))-(3N -1.8)<a<(5N/9(N-1)) (3N -0.9),respectively (N is the number of nodes in the network ). A class of the distributed routing algorithms for the DOLDL and the implementation procedure of an adaptive fault-tolerant algorithm are proposed and analyzed. The correctness of the algorithm has also been verified by simulating.