Xiao-Feng Xie

Xiao-Feng Xie
WIOMAX

Ph.D.

About

51
Publications
8,419
Reads
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1,890
Citations
Citations since 2017
7 Research Items
613 Citations
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2017201820192020202120222023020406080100
2017201820192020202120222023020406080100
2017201820192020202120222023020406080100
Introduction
Co-Founder @WIOMAX: Focus broadly on creating smart and scalable optimization solutions in sustainable transportation, smart cities, and Internet of Things (IoT)

Publications

Publications (51)
Preprint
Full-text available
We perform a systematic analysis on the large-scale taxi trip data to uncover urban mobility and city dynamics in multimodal urban transportation environments. As a case study, we use the taxi origin-destination trip data and some additional data sources in Washington DC area. We first study basic characteristics of taxi trips, then focus on five i...
Preprint
Full-text available
In this paper, we present a method using AI techniques to solve a case of pure mathematics applications for finding narrow admissible tuples. The original problem is formulated into a combinatorial optimization problem. In particular, we show how to exploit the local search structure to formulate the problem landscape for dramatic reductions in sea...
Article
We present a combined traffic control and route choice optimization (CTCRCO) system to quickly find new traffic equilibrium solutions in urban road networks with significant changes. The system iteratively executes a control module which combines a traffic control system (TCS) and a traffic simulation manager (TSM) and an assignment module which co...
Technical Report
Full-text available
We perform a systematic analysis on the large-scale taxi trip data to uncover urban mobility and city dynamics in multimodal urban transportation environments. As a case study, we use the taxi origin-destination trip data and some additional data sources in Washington DC area. We first study basic characteristics of taxi trips, then focus on five i...
Article
Full-text available
Bikesharing has gradually become an adopted form of mobility in urban area recent years as one sustainable transportation mode to bring us many social, environmental, economic, and health-related benefits and rewards. There is increased research toward better understanding of bikesharing systems (BSS) in urban environments. However, our comprehensi...
Article
In this paper, we present a Smart In-Vehicle Decision Support System (SIV-DSS) to help making better stop/go decisions in the indecision zone as a vehicle is approaching a signalized intersection. Supported by the Vehicle-to-Infrastructure (V2I) communications, the system integrates and utilizes the information from both vehicle and intersection. T...
Technical Report
Full-text available
The smart IoT is dramatically accelerating the pace of innovation and transforming the way of operations in transportation and infrastructure. The ubiquitous deployment of smart, connected sensors and things, combined with artificial intelligence (AI) and big data analytics, can enable us to gather insightful knowledge, make real-time and even pred...
Article
Full-text available
We present CGO-AS, a generalized Ant System (AS) implemented in the framework of Cooperative Group Optimization (CGO), to show the leveraged optimization with a mixed individual and social learning. Ant colony is a simple yet efficient natural system for understanding the effects of primary intelligence on optimization. However, existing AS algorit...
Conference Paper
Full-text available
In this paper, we present a method using AI techniques to solve a case of pure mathematics applications for finding narrow admissible tuples. The original problem is formulated into a combinatorial optimization problem. In particular, we show how to exploit the local search structure to formulate the problem landscape for dramatic reductions in sea...
Article
This paper adopts an unsupervised learning approach, k-means clustering, to analyze the arterial traffic flow data over a highdimensional spatiotemporal feature space. As part of the adaptive traffic control system deployed around the East Liberty area in Pittsburgh, high-resolution traffic occupancies and counts are available at the lane level in...
Conference Paper
Full-text available
The rapid rise of location-based services provides us an opportunity to achieve the information of human mobility, in the form of participatory sensing, where users can share their digital footprints (i.e., checkins) at different geo-locations (i.e., venues) with timestamps. These checkins provide a broad citywide coverage, but the instant number o...
Article
Full-text available
We prove distribution estimates for primes in arithmetic progressions to large smooth squarefree moduli, with respect to congruence classes obeying Chinese remainder theorem conditions, obtaining an exponent of distribution 12+7/300.
Article
Full-text available
The route choice system and the traffic control system (TCS) constitute two major approaches to mitigating congestion in urban road networks. The interaction between signal control and route choice is considered from a narrower route choice system perspective, with the focus on route choice models for operational purposes. The goal is to analyze th...
Article
Full-text available
In this paper, a round-table group optimization (RTGO) algorithm is presented. RTGO is a simple metaheuristic framework using the insights of research on group creativity. In a cooperative group, the agents work in iterative sessions to search innovative ideas in a common problem landscape. Each agent has one base idea stored in its individual memo...
Conference Paper
Traffic congestion significantly degrades the quality of life in urban environments. It results in lost time, wasted fuel resources and reduced air quality for urban residents. Recent work in real-time, schedule-driven control of traffic signal networks has introduced new possibilities for reducing congestion in urban environments. However so far,...
Article
Full-text available
A cooperative group optimization (CGO) system is presented to implement CGO cases by integrating the advantages of the cooperative group and low-level algorithm portfolio design. Following the nature-inspired paradigm of a cooperative group, the agents not only explore in a parallel way with their individual memory, but also cooperate with their pe...
Conference Paper
Full-text available
It is very important to understand human mobility and activity patterns in urban environments. In smart traffic control systems, abundant traffic flow data could be collected over time by physical sensing. However, each controlled region only covers a small area, and there is no user information in the data. The rapid rise of location-based service...
Article
Model-based intersection optimization strategies have been widely investigated for distributed traffic signal control in road networks. Due to the form of “black-box” optimization that is typically assumed, a basic challenge faced by these strategies is the combinatorial nature of the problem that must be solved. The underlying state space is expon...
Conference Paper
Full-text available
We take an agent-based approach to real-time traffic signal control based on coordinated look-ahead scheduling. At each decision point, each agent constructs a schedule that optimizes movement of the currently approaching traffic through its intersection. For strengthening its local view, each agent queries the scheduled outflows from its direct up...
Article
Full-text available
Real-time optimization of the dynamic flow of vehicle traf-fic through a network of signalized intersections is an im-portant practical problem. In this paper, we take a decentral-ized, schedule-driven coordination approach to address the challenge of achieving scalable network-wide optimization. To be locally effective, each intersection is contro...
Conference Paper
Full-text available
In this paper, we take a self-scheduling approach to solving the traffic signal control problem, where each intersection is controlled by a self-interested agent operating with a limited (fixed horizon) view of incoming traffic. Central to the approach is a representation that aggregates incoming vehicles into critical clusters, based on the non-un...
Article
Full-text available
A multiagent fusion search is presented for the graph coloring problem. In this method, each of agents performs the fusion search, involving a local search working in a primary exploitation role and a recombination search in a navigation role, with extremely limited memory and interacts with others through a decentralized protocol, thus agents are...
Article
Full-text available
The multiagent optimization system (MAOS) is a nature-inspired method, which supports cooperative search by the self-organization of a group of compact agents situated in an environment with certain sharing public knowledge. Moreover, each agent in MAOS is an autonomous entity with personal declarative memory and behavioral components. In this pape...
Article
Full-text available
To enhance the quality of solutions for the problems with equality constraints in evolutionary optimization, a paradigm of multi-stage dynamic shrinking strategy (MS-DSS) is proposed by partitioning the evolutionary process into three stages: a) exploring, b) approaching, and c) exploiting stage, to shrink the violation values to an expected value...
Article
With e-business emerging as a key enabler to drive supply chains, the focus of supply chain management has been shifted from production efficiency to customer-driven and partnership synchronization approaches. This strategic shift depends on the match between the demands and offerings that deliver the services. To achieve this, we need to coordinat...
Conference Paper
Full-text available
The 0-1 quadratic knapsack problem (QKP) is a hard computational problem, which is a generalization of the knapsack problem (KP). In this paper, a mini-swarm system is presented. Each agent, realized with minor declarative knowledge and simple behavioral rules, searches on a structural landscape of the problem through the guided generate-and-test b...
Conference Paper
Full-text available
E-service/process composition requires allocating suitable resources to a set of services that constitute a composite service/process. The problem is complicated due to undetermined constraints of each component service and unpredictable solutions contributed by service providers. It needs the ability to rapidly identify the suitable solutions as w...
Conference Paper
Full-text available
The hard computational problems, such as the traveling salesman problem (TSP), are relevant to many tasks of practical interest, which normally can be well formalized but are difficult to solve. This paper presents an extended multiagent optimization system, called MAOS E , for supporting cooperative problem solving on a virtual landscape and achie...
Conference Paper
Full-text available
A compact multiagent optimization system (MAOS<sub>C</sub>) based on autonomy oriented computing (AOC) is presented. Performed by a society of autonomous entities in iterative cycles, an optimization algorithm can simply be described by a macro generate-and-test behavior, which deploys a few elemental generating behaviors under conditioned reflex b...
Article
Full-text available
A self-organizing particle swarm is presented. It works in dissipative state by employing the small inertia weight, according to experimental analysis on a simplified model, which with fast convergence. Then by recognizing and replacing inactive particles according to the process deviation information of device parameters, the fluctuation is introd...
Article
Full-text available
The Periodic mode is analyzed together with two conventional boundary handling modes for particle swarm. By providing an infinite space that comprises periodic copies of original search space, it avoids possible disorganizing of particle swarm that is induced by the undesired mutations at the boundary. The results on benchmark functions show that p...
Article
Full-text available
A dissipative particle swarm optimization is developed according to the self-organization of dissipative structure. The negative entropy is introduced to construct an opening dissipative system that is far-from-equilibrium so as to driving the irreversible evolution process with better fitness. The testing of two multimodal functions indicates it i...
Article
The adaptive constraints relaxing rule for swarm algorithms to handle with the problems with equality constraints is presented. The feasible space of such problems may be similiar to ridge function class, which is hard for applying swarm algorithms. To enter the solution space more easily, the relaxed quasi feasible space is introduced and shrinked...
Conference Paper
Full-text available
A self-organizing particle swarm is presented. It works in dissipative state by employing the small inertia weight, according to experimental analysis on a simplified model, which with fast convergence. Then by recognizing and replacing inactive particles according to the process deviation information of device parameters, the fluctuation is introd...
Conference Paper
Full-text available
The adaptive constraints relaxing rule for swarm algorithms to handle with the problems with equality constraints is presented. The feasible space of such problems may be similiar to ridge function class, which is hard for applying swarm algorithms. To enter the solution space more easily, the relaxed quasi feasible space is introduced and shrinked...
Conference Paper
Full-text available
A swarm algorithm framework (SWAF), realized by agent-based modeling, is presented to solve numerical optimization problems. Each agent is a bare bones cognitive architecture, which learns knowledge by appropriately deploying a set of simple rules in fast and frugal heuristics. Two essential categories of rules, the generate-and-test and the proble...
Conference Paper
Swarm systems are products of natural evolution. The complex collective behavior can emerge from a society of N autonomous cognitive entities [2], called as agents [5]. Each agent acquires knowledge in socially biased individual learning [4]. For human, the extrasomatic arbitrary symbols that manipulated by language allows for cognition on a grand...
Article
The parameter selection of differential evolution (DE) is studied by experiments on some benchmark examples. A simplified DE version (SDE) is realized with randomized scaling factor F based on the analysis for the features of DE, which not only reduces a parameter, but also is flexible for the selection of parameter CR. The experiments by comparing...
Conference Paper
Full-text available
A hybrid particle swarm with differential evolution operator, termed DEPSO, which provide the bell-shaped mutations with consensus on the population diversity along with the evolution, while keeping the self-organized particle swarm dynamics, is proposed. Then it is applied to a set of benchmark functions, and the experimental results illustrate it...
Article
The developments and applications related to particle swarm optimization (PSO) are discussed. Firstly, developments in the particle swarm optimization since 1995 are reviewed. Then parameter settings are analyzed systematically according to some existed testing results. Some improvement methods, such as cluster analysis, selection, neighborhood ope...
Article
Full-text available
In this presented paper, to accomplish semiconductor device synthesis for TCAD application, the Parallel Genetic Algorithm is applied as the core searching algorithm for "acceptability region" of device designables, which satisfy the designed device performance. The results of some experiments on FIBMOS are shown, which indicate the Parallel Geneti...
Conference Paper
Full-text available
An adaptive particle swarm optimization (PSO) on individual level is presented. By analyzing the social model of PSO, a replacement criterion, based on the diversity of fitness between the current particle and the best historical experience, is introduced to maintain the social attribution of swarm adaptively by taking off inactive particles. The t...
Article
Device robust-design is inherently a multiple-objective optimization problem. Using design of experiments (DoE) combined with response surface methodology (RSM) can satisfy the great incentive to reduce the number of TCAD simulations that need to be performed. However, the errors of RSM models may large enough to diminish the validity of the result...
Article
The genetic algorithm, called GENOCOP, used in the semiconductor device comprehensive system is improved. The real-valued design space is transformed into integer-valued design space according to the effects of the technical precision of the processing parameters. An adaptive combined operator is introduced to extend and exploit the quasi-feasible...
Conference Paper
Full-text available
Process synthesis is a top-down design methodology and can effectively reduce the process design time. In the paper the general method and the neural network (NN) package used for process synthesis are discussed. Then the characteristics of synthesizing some key process modules, including ion implantation and well formation, are analyzed, based on...
Conference Paper
Full-text available
Social cognitive optimization (SCO) for solving nonlinear programming problems (NLP) is presented based on human intelligence with the social cognitive theory (SCT). Experiments comparing SCO with genetic algorithms on some benchmark functions show that the former can produce high-quality solutions efficiently, even with only one learning agent.
Conference Paper
Full-text available
Abstract - The demand,for the solutions to different complex numerical optimization problems has long outstripped the ability of engineers to supply them. Since the numerical optimization is a static problem that is ,naturally similar to the,movement ,of particulates with particle-wave,duality in potential field, it can be simulated by the assistan...
Conference Paper
Full-text available
A hybrid particle swarm optimizer with mass extinction, which has been suggested to be an important mechanism for evolutionary progress in the biological world, is presented to enhance the capacity in reaching an optimal solution. The tested results of three benchmark functions indicate this method improves the performance effectively.
Conference Paper
Full-text available
In this presented paper, to accomplish semiconductor device synthesis for TCAD application, the Parallel Genetic Algorithm is applied as the core searching algorithm for "acceptability region" of device designables, which satisfy the designed device performance. The results of some experiments on FIBMOS are shown, which indicate the Parallel Geneti...

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