World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
48
Citations
15419
World Ranking
6033
National Ranking
2715

Mathematics

D-Index
46
Citations
14574
World Ranking
1321
National Ranking
592

Research.com Recognitions

  • 2017 - IEEE Fellow For contributions to computational intelligence for complex systems

Overview

Alice E. Smith is affiliated with Auburn University in the United States and has contributed extensively to the field of engineering with a particular focus on industrial and manufacturing engineering. Their research addresses topics related to vehicle routing optimization, transportation and mobility innovations, and advanced manufacturing and logistics optimization. Additional areas of interest include UAV applications and optimization, urban and freight transport logistics, as well as optimization and packing problems.

Smith's recent publications illustrate a consistent engagement with logistics and optimization in transport systems. Notable papers include "The traveling salesman problem with release dates and drone resupply" (2020, Computers & Operations Research), "Sustainable last mile parcel delivery and return service using drones" (2023, Engineering Applications of Artificial Intelligence), and "A tabu search algorithm to solve a green logistics bi-objective bi-level problem" (2021, Annals of Operations Research). Other publications are "Dynamic vehicle routing problem with drone resupply for same-day delivery" (2024, Transportation Research Part C Emerging Technologies) and "A computational software system to design order picking warehouses" (2021, Computers & Operations Research).

The frequent co-authors collaborating with Smith are Daniel F. Silva, Juan C. Pina-Pardo, Kevin R. Gue, Molly Marino, and Anne Deutsch. These collaborations appear across multiple projects reflecting an interdisciplinary and team-oriented research environment.

Smith's work is regularly published in a variety of respected scientific venues. These include:

  • INFORMS Journal on Computing
  • IEEE Computational Intelligence Magazine
  • Computers & Operations Research
  • European Journal of Operational Research
  • Computers & Industrial Engineering

Their research contributions span a range of engineering subfields, notably:

  • Industrial and Manufacturing Engineering
  • Aerospace Engineering
  • Automotive Engineering
  • Building and Construction
  • Computer Networks and Communications

Smith has also contributed to academic books, including a publication with Springer International Publishing titled Women in Computational Intelligence (2022).

Among their recognized professional achievements is the IEEE Fellow award received in 2017 for contributions to computational intelligence for complex systems.

Best Publications

  • Multi-objective optimization using genetic algorithms: A tutorial

    Abdullah Konak;David W. Coit;Alice E. Smith

  • COST ESTIMATION PREDICTIVE MODELING: REGRESSION VERSUS NEURAL NETWORK

    Alice E. Smith;Anthony K. Mason

  • Reliability optimization of series-parallel systems using a genetic algorithm

    D.W. Coit;A.E. Smith

  • A genetic approach to the quadratic assignment problem

    David M. Tate;Alice E. Smith

  • An ant colony optimization algorithm for the redundancy allocation problem (RAP)

    Yun-Chia Liang;A.E. Smith

  • Local search genetic algorithm for optimal design of reliable networks

    B. Dengiz;F. Altiparmak;A.E. Smith

  • EFFICIENTLY SOLVING THE REDUNDANCY ALLOCATION PROBLEM USING TABU SEARCH

    Sadan Kulturel-Konak;Alice E. Smith;David W. Coit

  • Unequal-area facility layout by genetic search

    David M. Tate;Alice E. Smith

  • Penalty guided genetic search for reliability design optimization

    David W. Coit;Alice E. Smith

  • Genetic Optimization Using A Penalty Function

    Alice E. Smith;David M. Tate

  • Adaptive Penalty Methods for Genetic Optimization of Constrained Combinatorial Problems

    David W. Coit;Alice E. Smith;David M. Tate

  • Efficient optimization of all-terminal reliable networks, using an evolutionary approach

    B. Dengiz;F. Altiparmak;A.E. Smith

  • A Seeded Memetic Algorithm for Large Unit Commitment Problems

    Jorge Valenzuela;Alice E. Smith

  • X-bar and R control chart interpretation using neural computing

    Alice E. Smith

  • Solving the redundancy allocation problem using a combined neural network/genetic algorithm approach

    David W. Coit;Alice E. Smith

  • Estimation of all-terminal network reliability using an artificial neural network

    Chat Srivaree-ratana;Abdullah Konak;Alice E. Smith

  • STATIC NEURAL NETWORK PROCESS MODELS : CONSIDERATIONS AND CASE STUDIES

    D. W. Coit;B.T. Jackson;A.E. Smith

  • Bias and variance of validation methods for function approximation neural networks under conditions of sparse data

    J.M. Twomey;A.E. Smith

  • A new mixed integer programming formulation for facility layout design using flexible bays

    Abdullah Konak;Sadan Kulturel-Konak;Bryan A. Norman;Alice E. Smith

  • Expected Allele Coverage and the Role of Mutation in Genetic Algorithms

    David M. Tate;Alice E. Smith

Frequent Co-Authors

Bryan A. Norman
Bryan A. Norman Texas Tech University
David W. Coit
David W. Coit Rutgers, The State University of New Jersey
Mitsuo Gen
Mitsuo Gen Tokyo University of Science

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