An analytical method to calculate station evacuation capacity

The major objective of this work was to calculate evacuation capacity and solve the optimal routing problem in a given station topology from a network optimization perspective where station facilities were modelled as open finite queueing networks with a multi-objective set of performance measures. The optimal routing problem was determined so that the number of evacuation passengers was maximized while the service level was higher than a certain criterion. An analytical technique for modelling open finite queueing networks, called the iteration generalized expansion method(IGEM), was utilized to calculate the desired outputs. A differential evolution algorithm was presented for determining the optimal routes. As demonstrated, the design methodology which combines the optimization and analytical queueing network models provides a very effective procedure for simultaneously determining the service level and the maximum number of evacuation passengers in the best evacuation routes.

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 GA approach to vehicle routing problem with time windows considering loading constraints

As a new variant of vehicle routing problem( VRP),a finished vehicle routing problem with time windows in finished vehicle logistics( FVRPTW) is modeled and solved. An optimization model for FVRPTW is presented with the objective of scheduling multiple transport routes considering loading constraints along with time penalty function to minimize the total cost. Then a genetic algorithm( GA) is developed. The specific encoding and genetic operators for FVRPTW are devised.Especially,in order to accelerate its convergence,an improved termination condition is given. Finally,a case study is used to evaluate the effectiveness of the proposed algorithm and a series of experiments are conducted over a set of finished vehicle routing problems. The results demonstrate that the proposed approach has superior performance and satisfies users in practice. Contributions of the study are the modeling and solving of a complex FVRPTW in logistics industry.

Multi-strategy Differential Evolution Algorithm for QoS Multicast Routing

This paper studies the difference algorithm parameters characteristic of the multicast routing problem, and to compare it with genetic algorithms. The algorithm uses the path of individual coding, combined with the differential cross-choice strategy and operations optimization. Finally, we simulated 30 node networks, and compared the performance of genetic algorithm and differential evolution algorithm. Experimental results show that multi-strategy Differential Evolution algorithm converges faster and better global search ability and stability.

A Quantum Algorithm for Finding a Hamilton Circuit

A quantum algorithm for solving the classical NP-complete problem - the Hamilton circuit is presented. The algorithm employs the quantum SAT and the quantum search algorithms. The algorithm is square-root faster than classical algorithm, and becomes exponentially faster than classical algorithm if nonlinear quantum mechanical computer is used.

Robot Positioning and Navigation Based on Hybrid Wireless Sensor Network

Traditional sensor network and robot navigation are based on the map of detecting the fields available in advance. The optimal algorithms are developed to solve the energy saving, the shortest path problems, etc. However, in the practical enviroranent, there are many fields, whose map is difficult to get, and needs to be detected. In this paper a kind of ad-hoc navigation algorithm is explored, which is based on the hybrid sensor network without the prior map in advance. The navigation system is composed of static nodes and dynamic trades. The static nodes monitor the occurrances of the events and broadcast them. In the syston, a kind of algorithm is to locate the rdbot, which is based on duster broadcasting. The dynamic nodes detect the adversary or dangerous fields and broadcast warning messages. The robot gets the message and follows ad-hoc routine to arrive where the events occur. In the whole process, energy saving has been taken into account. The algorithms, which are based on the hybrid sensor network, are given in this paper. The simulation and practical results are also available.

A Two-phase Solution Algorithm for the Inventory Routing Problem with Time Windows

The main objective of this paper is to propose a two-phase solution algorithm for solving the Inventory Routing Problem with Time Windows （IRPTW）, which has not been excessively researched in the literature. The solution approach is based on （a） a simple simulation for the planning phase （Phase I） and （b） the Variable Neighborhood Search Algorithm （VNS） for the routing phase （Phase II）. Testing instances are established to investigate algorithmic performance, and the computational results are then reported. The computational study underscores the importance of integrating the inventory and vehicle routing decisions. Graphical presentation formats are provided to convey meaningful insights into the problem.

Dynamic services selection algorithm in Web services composition supporting cross-enterprises collaboration

Based on the deficiency of time convergence and variability of Web services selection for services composition supporting cross-enterprises collaboration,an algorithm QCDSS(QoS constraints of dynamic Web services selection)to resolve dynamic Web services selection with QoS global optimal path,was proposed.The essence of the algorithm was that the problem of dynamic Web services selection with QoS global optimal path was transformed into a multi-objective services composition optimization problem with QoS constraints.The operations of the cross and mutation in genetic algorithm were brought into PSOA(particle swarm optimization algorithm),forming an improved algorithm(IPSOA)to solve the QoS global optimal problem.Theoretical analysis and experimental results indicate that the algorithm can better satisfy the time convergence requirement for Web services composition supporting cross-enterprises collaboration than the traditional algorithms.

Best compromising crashworthiness design of automotive S-rail using TOPSIS and modified NSGAⅡ

In order to reduce both the weight of vehicles and the damage of occupants in a crash event simultaneously, it is necessary to perform a multi-objective optimal design of the automotive energy absorbing components. Modified non-dominated sorting genetic algorithm II(NSGA II) was used for multi-objective optimization of automotive S-rail considering absorbed energy(E), peak crushing force(Fmax) and mass of the structure(W) as three conflicting objective functions. In the multi-objective optimization problem(MOP), E and Fmax are defined by polynomial models extracted using the software GEvo M based on train and test data obtained from numerical simulation of quasi-static crushing of the S-rail using ABAQUS. Finally, the nearest to ideal point(NIP)method and technique for ordering preferences by similarity to ideal solution(TOPSIS) method are used to find the some trade-off optimum design points from all non-dominated optimum design points represented by the Pareto fronts. Results represent that the optimum design point obtained from TOPSIS method exhibits better trade-off in comparison with that of optimum design point obtained from NIP method.

Antiretroviral Drug Distribution Routing System in Limpopo Province of South Africa

This study was concerned with developing an antiretroviral drug distribution routing system with a goal of improving fleet utilization whilst reducing delivery costs. The system would enhance ARV drug delivery satisfaction of patients staying in the Limpopo province of South Africa. A VRP mathematical programming problem was formulated and the Savings Based as well as the Sequential Insertion algorithm was used to solve the problem. A mini program was then developed in Visual Basic.Net software that speeded up the vehicle route determination heuristics. This computer based vehicle routing system gave a total travelled distance of 1302.94 km and a space utilization of 93% as compared to the pigeonhole system which had a total travelled distance of 2874.2 km and space utilization of 86% for the demand of 5384 ARV drug patients. Therefore, the mathematical programming approach is more cost effective and efficient thereby enhancing delivery satisfaction to ARV drug patients in the province.

Speedup in adiabatic evolution based quantum algorithms

In this context,we study three different strategies to improve the time complexity of the widely used adiabatic evolution algorithms when solving a particular class of quantum search problems where both the initial and final Hamiltonians are one-dimensional projector Hamiltonians on the corresponding ground state.After some simple analysis,we find the time complexity improvement is always accompanied by the increase of some other "complexities" that should be considered.But this just gives the implication that more feasibilities can be achieved in adiabatic evolution based quantum algorithms over the circuit model,even though the equivalence between the two has been shown.In addition,we also give a rough comparison between these different models for the speedup of the problem.

Reliability assessment of networks-on-chip based on analytical models

As technology scales down, the reliability issues are becoming more crucial, especially for networks-on-chip (NoCs) that provide the communication requirements of multi-processor systems-on-chip. Reliability evaluation based on analytical models is a precise method for dependability analysis before and after designing the fault-tolerant systems. In this paper, we accurately formulate the inherent reliability and vulnerability of some popular NoC architectures against permanent faults, also depending on the employed routing algorithm and traffic model. Based on this analysis, effects of failures in the links, switches and network interfaces on the packet delivery of NoCs are determined. Besides, some extensions to evaluate a fault-tolerant method and some routing algorithms are described. The analyses are validated through appropriate simulations. The results thus obtained are exactly the same as or very close to the analytical ones.

Simplifying the Nonlinear Continuous Time-Cost Tradeoff Problem

Equivalent simplification is an effective method for solving large-scale complex problems. In this paper, the authors simplify a classic project scheduling problem, which is the nonlinear continuous time-cost tradeoff problem(TCTP). Simplifying TCTP is a simple path problem in a critical path method(CPM) network. The authors transform TCTP into a simple activity float problem and design a complex polynomial algorithm for its solution. First, the authors discover relationships between activity floats and path lengths by studying activity floats from the perspective of path instead of time.Second, the authors perform simplification and improve the efficiency and accuracy of the solution by deleting redundant activities and narrowing the duration intervals of non-redundant activities. Finally,the authors compare our method with current methods. The relationships between activity floats and path lengths provide new approaches for other path and correlative project problems.

A complementary formulation for traffic equilibrium problem with a new nonadditive route cost

Improviag transportation system is essential for all people in each city since transport plays a very important role. Using mathematical programming approach transport problem is an effective way to improve transportation system. In this paper, the traffic equilibrium problem （TEP） with a general nonadditive route cost function is studied. We formulate the route cost function for each route as a disutility function, which can evaluate route cost function flexibly and analyze the route toll conveniently. Furthermore, we present the TEP with a nonlinear complementary problem （NCP） formulation. The monotonicity and the existence with the NCP formulation are also given under relative assumptions.