The interval min–max regret knapsack packing-delivery problem-Reference-Cited by-同舟云学术

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The interval min–max regret knapsack packing-delivery problem

Published:2020-07-14 Issue:18 Volume:59 Page:5661-5677
ISSN:0020-7543
Container-title:International Journal of Production Research
language:en
Short-container-title:International Journal of Production Research

Author:

Wang Shijin¹,Cui Wenli¹,Chu Feng²³,Yu Jianbo⁴

Affiliation:

1. School of Economics and Management, Tongji University, Shanghai, People's Republic of China

2. Laboratoire IBISCUniv-Évry, Université Paris-Saclay, Évry, France

3. School of Economics and Management, Fuzhou University, Fuzhou, People's Republic of China

4. School of Mechanical Engineering, Tongji University, Shanghai, People's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Industrial and Manufacturing Engineering,Management Science and Operations Research,Strategy and Management

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207543.2020.1789235

Reference41 articles.

1. A quantitative analysis of the simulated annealing algorithm: A case study for the traveling salesman problem

2. Approximation of min–max and min–max regret versions of some combinatorial optimization problems

3. Complexity of the min–max (regret) versions of min cut problems

4. Min–max and min–max regret versions of combinatorial optimization problems: A survey

5. Minmax Regret Median Location on a Network Under Uncertainty

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2. A 0–1 knapsack problem-based approach for solving open-pit mining problem with type-2 fuzzy parameters;Innovations in Systems and Software Engineering;2022-11-19

3. Solving a Mathematical Model for Small Vegetable Sellers in India by a Stochastic Knapsack Problem: An Advanced Genetic Algorithm Based Approach;International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems;2022-10

4. Knapsack problems — An overview of recent advances. Part I: Single knapsack problems;Computers & Operations Research;2022-07

5. Robust (min–max regret) single machine scheduling with interval processing times and total tardiness criterion;Computers & Industrial Engineering;2020-11

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