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Paper Citation Record · LEDGER

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization

As of 8 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2506.09404.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.09404 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:58:22.562491Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

50 of 50 outbound references displayed

  • verified exact7
  • verified fuzzy25
  • unresolved18
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation db6b1258-b971-4d9d-b4b8-1ccab4ca1de1 · outbound

This paper cites an unresolved cited work.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Unresolved cited work

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation b71eb87e-c128-4c7c-9f1a-d18035b400ae · outbound

This paper cites Learning what to defer for maximum in- dependent sets.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Learning what to defer for maximum in- dependent sets

Reference 2

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source=pdf_text observed=2026-08-07T04:58:17.797771Z digest=sha256:f2241ab3fc9cb03290945e5cfb3bcfd5724b2ff4d27ae6ca45b8d9cdc84f756c

Observation 503d1094-3a71-440d-8371-ef96abdebb57 · outbound

This paper cites an unresolved cited work.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Unresolved cited work

Reference 3

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation a53670c3-74e3-4c56-a9b0-db32043498d1 · outbound

This paper cites Princeton university press, 2006.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Princeton university press, 2006

Reference 4

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raw_fallback, observed 2026-08-07T04:58:40.075604Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:17.929684Z digest=sha256:f732659abce3f9dbf81c7dab4b232b0ed3d7a7786d5e99b215aca63f729f9a36

Observation 0945ebad-4b76-4480-a4dc-02f10b570a97 · outbound

This paper cites The prize collecting traveling salesman problem.Networks, 19(6):621–636, 1989.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization The prize collecting traveling salesman problem.Networks, 19(6):621–636, 1989

Reference 5

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raw_fallback, observed 2026-08-07T04:58:36.382864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:18.001120Z digest=sha256:0e83f626eb7829c074897d6a2671ad6e680ab1d8fb8e9a23ed94a14705d82553

Observation 4a76f63d-23fa-4969-903f-5b6ee5bfc33c · outbound

This paper cites Neural Combinatorial Optimization with Reinforcement Learning.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Neural Combinatorial Optimization with Reinforcement Learning

Reference 6

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no resolver link, observed 2026-08-07T04:58:18.087265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:58:18.087265Z digest=sha256:63d42a57f983d6eb490be841b50af92da18e6d7432f60d11fd58d5bdd5082ca6

Observation 6fdd55cb-a373-4ab5-a7dd-701670fba149 · outbound

This paper cites Routefinder: Towards foundation models for vehicle routing problems.arXiv preprint arXiv:2406.15007, 2024.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Routefinder: Towards foundation models for vehicle routing problems.arXiv preprint arXiv:2406.15007, 2024

Reference 7

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no resolver link, observed 2026-08-07T04:58:18.160667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:58:18.160667Z digest=sha256:a4ded072e4be7cfd208f1a6d7024bff4156ad50f7f0b4e4d12d9a8607d254174

Observation 4307d19d-6b10-49bd-8b0a-86eb1cdb1b3f · outbound

This paper cites Reinforcement Learning Driven Heuristic Optimization.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Reinforcement Learning Driven Heuristic Optimization

Reference 8

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verified exact
local_arxiv, observed 2026-08-07T04:58:24.436474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:18.306281Z digest=sha256:139022ee192658fbba85cd3286ae55267d8747fe34f8080fb707412d3a9bcb6e

Observation 92197eae-ff98-4617-beef-859bcf6b6a25 · outbound

This paper cites Learning to perform local rewriting for combinatorial optimization.Advances in neural information processing systems, 32, 2019.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Learning to perform local rewriting for combinatorial optimization.Advances in neural information processing systems, 32, 2019

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:18.332986Z digest=sha256:2431d4eff68b1f6f1fc1e1a3a6a61bdbdc77b29faa3a17a5ec654e873bfb7b87

Observation de8e6af4-f332-4428-bc42-f37c5eff5cd1 · outbound

This paper cites A method for solving traveling-salesman problems.Operations research, 6 (6):791–812, 1958.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization A method for solving traveling-salesman problems.Operations research, 6 (6):791–812, 1958

Reference 10

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raw_fallback, observed 2026-08-07T04:58:30.452119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:18.401837Z digest=sha256:23d1f1cbf63a38d56d9b63129fcf0068fdfa2cd13f989341f52c18e924ea597e

Observation c57b41b6-af72-482e-8fcc-f178869d404f · outbound

This paper cites Learning 2-opt heuristics for the traveling salesman problem via deep reinforcement learning.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Learning 2-opt heuristics for the traveling salesman problem via deep reinforcement learning

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:18.465834Z digest=sha256:687dc9f7403c7505cba87a9cb2308e5cc2f0a01730c644db00c8135a81bb5e53

Observation f7400ad2-3022-4b11-9fbd-a6ee47945788 · outbound

This paper cites Handbook of genetic algorithms.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Handbook of genetic algorithms

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:18.515815Z digest=sha256:960d8a47f53b8f67f55a3a55ceefe3014e5c40b2ee48eeec535e4396d4d84b16

Observation 39c2cc19-d945-409f-8113-171288e1dd85 · outbound

This paper cites University of Michigan, 1975.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization University of Michigan, 1975

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:58:18.575714Z digest=sha256:8fe3eb34d75e595ea6f8811d32adea8a5b8077c1ab1c7bc129e58550b984517c

Observation f2402424-edf7-42ba-9178-0f0d24dace0d · outbound

This paper cites Design paradigms of intelligent control systems on a chip.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Design paradigms of intelligent control systems on a chip

Reference 14

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local_arxiv, observed 2026-08-07T04:58:24.180850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:18.641727Z digest=sha256:96a100e92946412bc055b9e87e330c264afce28cb4d4c73ed1e2d2962c41025b

Observation 233cc5ee-f904-448f-8ed8-810e046d418f · outbound

This paper cites Designing an Optimal Portfolio for Iran's Stock Market with Genetic Algorithm using Neural Network Prediction of Risk and Return Stocks.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Designing an Optimal Portfolio for Iran's Stock Market with Genetic Algorithm using Neural Network Prediction of Risk and Return Stocks

Reference 15

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verified exact
local_arxiv, observed 2026-08-07T04:58:23.880583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:18.687024Z digest=sha256:dd9c0a4d0b6d320055c9b5d70cb83feab448b5ab66832ddd8ac372804328eb76

Observation dcc16989-1614-43c4-98b1-0b8abef11f6e · outbound

This paper cites Alleleslociand the traveling salesman problem.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Alleleslociand the traveling salesman problem

Reference 16

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raw_fallback, observed 2026-08-07T04:58:29.557012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:18.767610Z digest=sha256:b98fb252f88c7c65b94804bf900763ce1600c289bd13aa0a3f43e05b19d525e5

Observation 773f1c37-fb51-4da9-a369-27b45a224cc6 · outbound

This paper cites The orienteering problem.Naval Research Logistics (NRL), 34(3):307–318, 1987.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization The orienteering problem.Naval Research Logistics (NRL), 34(3):307–318, 1987

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:18.819283Z digest=sha256:ceddc3dbc8965ebdae1bfae4a4fefde4e46e3c2d2d70dc0d0e01fcd94040832d

Observation 365742be-ffdd-43c3-8864-3c42febf92de · outbound

This paper cites Accelerating vehicle routing via ai-initialized genetic algorithms.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Accelerating vehicle routing via ai-initialized genetic algorithms

Reference 18

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source=pdf_text observed=2026-08-07T04:58:18.887197Z digest=sha256:41a752e2292c97d914131d13d1742d143f679dbad2bdbd041554d126900a992c

Observation ad71c559-f996-419a-a464-43bf20510064 · outbound

This paper cites Winner takes it all: Training performant rl populations for combinatorial optimization.Advances in Neural Information Processing Systems, 36:48485–48509, 2023.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Winner takes it all: Training performant rl populations for combinatorial optimization.Advances in Neural Information Processing Systems, 36:48485–48509, 2023

Reference 19

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source=pdf_text observed=2026-08-07T04:58:18.948289Z digest=sha256:8d02a6ccae87559a66b023b8e3e69031c71c52e6cef08b4f51eff9a9b8b1c7c2

Observation 27c3bbca-e931-45cd-a01c-d6f3940c7db5 · outbound

This paper cites An extension of the lin-kernighan-helsgaun tsp solver for constrained traveling salesman and vehicle routing problems.Roskilde: Roskilde University, 12:966–980, 2017.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization An extension of the lin-kernighan-helsgaun tsp solver for constrained traveling salesman and vehicle routing problems.Roskilde: Roskilde University, 12:966–980, 2017

Reference 20

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source=pdf_text observed=2026-08-07T04:58:19.005827Z digest=sha256:f0670279406eb51126db228c8d10fbc24abd64e9f991a23e5a38c16f8e985bb4

Observation 1fbe2f60-5c4f-4189-9126-a367a9934733 · outbound

This paper cites Efficient Active Search for Combinatorial Optimization Problems.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Efficient Active Search for Combinatorial Optimization Problems

Reference 21

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source=pdf_text observed=2026-08-07T04:58:19.072722Z digest=sha256:8c287bbfb5a075f7aa5081800bcae87b7873ff51f47e4287f09fcfbb501bf3fb

Observation c1fa7188-bfd5-453c-a8a8-519e5b7ae904 · outbound

This paper cites Polynet: Learning diverse solution strategies for neural combinatorial optimization.arXiv preprint arXiv:2402.14048, 2024.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Polynet: Learning diverse solution strategies for neural combinatorial optimization.arXiv preprint arXiv:2402.14048, 2024

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:19.115621Z digest=sha256:bd65ddc7d6959cbd56674aab1faa7d5df10304f88c6b250c164d4a51d61c11b8

Observation 50e8be12-3b2b-4aa7-8db3-5394dae3c989 · outbound

This paper cites Constrained evolutionary optimization based on reinforcement learning using the objective function and constraints.Knowledge-Based Systems, 237:107731, 2022.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Constrained evolutionary optimization based on reinforcement learning using the objective function and constraints.Knowledge-Based Systems, 237:107731, 2022

Reference 23

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raw_fallback, observed 2026-08-07T04:58:28.967087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:19.166638Z digest=sha256:9b200e97f7315e3749ecdd838e6dba9b21a3bf40b4d831d9d853099a536224c7

Observation 4cdafdfb-361d-4ed5-86f5-5f9b8a3d7587 · outbound

This paper cites Evolution-guided policy gradient in reinforcement learning.Advances in Neural Information Processing Systems, 31, 2018.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Evolution-guided policy gradient in reinforcement learning.Advances in Neural Information Processing Systems, 31, 2018

Reference 24

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raw_fallback, observed 2026-08-07T04:58:28.662506Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:19.288980Z digest=sha256:8dbe91f99a6346602f58b67a89c045661f0409150fba38156a96c101115a31a4

Observation fcde1025-2446-44b5-9720-bc7117d981aa · outbound

This paper cites Learning collaborative policies to solve np-hard routing problems.Advances in Neural Information Processing Systems, 34:10418–10430, 2021.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Learning collaborative policies to solve np-hard routing problems.Advances in Neural Information Processing Systems, 34:10418–10430, 2021

Reference 25

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raw_fallback, observed 2026-08-07T04:58:28.380431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:19.464701Z digest=sha256:fa7849811733f2787202849e8616a940ee3774bad8e453d875bbb9d8162c9a26

Observation 51dc2c64-4a04-48c6-97f9-30c50a1ecd7e · outbound

This paper cites Sym-nco: Leveraging symmetricity for neural combinatorial optimization.Advances in Neural Information Processing Systems, 35:1936– 1949, 2022.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Sym-nco: Leveraging symmetricity for neural combinatorial optimization.Advances in Neural Information Processing Systems, 35:1936– 1949, 2022

Reference 26

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verified fuzzy
raw_fallback, observed 2026-08-07T04:58:28.193128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:19.642919Z digest=sha256:bd8361f7e0cbf2521158b3a99e1a1549ce779d6a0741581e490a03b64c3f8088

Observation 291bd41e-66c5-4469-a943-d3718dfa0e02 · outbound

This paper cites An efficient evolutionary algorithm for the orienteering problem.Computers & Operations Research, 90:42–59, 2018.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization An efficient evolutionary algorithm for the orienteering problem.Computers & Operations Research, 90:42–59, 2018

Reference 27

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raw_fallback, observed 2026-08-07T04:58:27.986223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:19.729357Z digest=sha256:a9153195c3cae22fc310e8da386dd262f89c8ece1f38067442945ba99fdf2b65

Observation 152f8dea-e66a-43ef-9cf6-49c4299c867d · outbound

This paper cites Attention, Learn to Solve Routing Problems!.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Attention, Learn to Solve Routing Problems!

Reference 28

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no resolver link, observed 2026-08-07T04:58:19.838303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:58:19.838303Z digest=sha256:8c71f4a58241df7ababb233a4628ce583f829cd6f72aaf17906c75348993ff48

Observation 65bb00a6-c83f-4928-beff-a24cac048416 · outbound

This paper cites Pomo: Policy optimization with multiple optima for reinforcement learning.Advances in Neural Information Processing Systems, 33:21188–21198, 2020.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Pomo: Policy optimization with multiple optima for reinforcement learning.Advances in Neural Information Processing Systems, 33:21188–21198, 2020

Reference 29

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no resolver link, observed 2026-08-07T04:58:19.991709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:58:19.991709Z digest=sha256:cc8beb0a1b3a7da5e591218082e73f89455868b6e959474587e1959aed0dede0

Observation 16d9c9b1-eea3-467c-b872-ed72e2d462eb · outbound

This paper cites Neurocrossover: An intelligent genetic locus selection scheme for genetic algorithm using reinforcement learning.Applied Soft Computing, 146:110680, 2023.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Neurocrossover: An intelligent genetic locus selection scheme for genetic algorithm using reinforcement learning.Applied Soft Computing, 146:110680, 2023

Reference 30

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raw_fallback, observed 2026-08-07T04:58:27.592957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:20.100107Z digest=sha256:40916f99f9640d50d8535600b59a84a4d7bf17bd00d350fb4d4baf7e924f3ff2

Observation 502adf96-255b-42ff-a0f5-7ee04a2ebef0 · outbound

This paper cites Iterated local search: Framework and applications.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Iterated local search: Framework and applications

Reference 31

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raw_fallback, observed 2026-08-07T04:58:27.319348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:20.246584Z digest=sha256:43a2fcedf52837580a855601011d010fbbb53d1bb8c941797deca84f8d2b7654

Observation 8352b01e-50d6-4299-a777-c869fa885e87 · outbound

This paper cites an unresolved cited work.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Unresolved cited work

Reference 32

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raw_fallback, observed 2026-08-07T04:58:26.911771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:20.371243Z digest=sha256:3ff1727273d2f76ad05a72cd20f52f240a9a507ce1fc3ccb927a24fdaab40c8f

Observation 6dc7292c-3e14-4066-a963-a7cc7d386c9f · outbound

This paper cites Learning to iteratively solve routing problems with dual-aspect collaborative transformer.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Learning to iteratively solve routing problems with dual-aspect collaborative transformer

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-07T04:58:26.662068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:20.584458Z digest=sha256:28570ed0919369f160d9c3b0b1a713e4443ac93ba65d8eab1b7aa8da3290c9b6

Observation 335f2af5-b2f1-4d70-a75f-dbc3c55c724d · outbound

This paper cites A hybrid genetic algorithm for the min–max multiple traveling salesman problem.Computers & Operations Research, 162:106455, 2024.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization A hybrid genetic algorithm for the min–max multiple traveling salesman problem.Computers & Operations Research, 162:106455, 2024

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:58:26.443927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:20.777880Z digest=sha256:4df7f6390e58ae4218050e596643ead3e159d95d862a22cafd3221b5a61ae785

Observation 0230addc-dc06-47c5-bc91-44ee7b6069e1 · outbound

This paper cites H-tsp: Hierarchically solving the large-scale traveling salesman problem.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization H-tsp: Hierarchically solving the large-scale traveling salesman problem

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:58:26.292045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:20.848063Z digest=sha256:e83c329a0d36741584b55e7097c542fc8db3e1b05643ede85a21100e9785304a

Observation 1d19dfbf-db4d-4a00-833a-63f11c2dcf16 · outbound

This paper cites Application of genetic algorithm in logistics management and distribution.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Application of genetic algorithm in logistics management and distribution

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:58:26.076714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:20.935139Z digest=sha256:20b89a81901bba40fe7c2c5d88abee567201491ac23d88c0dcb04694863883a9

Observation 61060cdf-7680-42bf-be1f-831b78ca9170 · outbound

This paper cites Rule-based reinforcement learning methodology to inform evolutionary algorithms for constrained optimization of engineering applications.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Rule-based reinforcement learning methodology to inform evolutionary algorithms for constrained optimization of engineering applications

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:58:25.811744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:21.016113Z digest=sha256:ccacc6a7e7a7a705858675d3482784de3fee5c2e8934c65ab45f25614c9fb8e1

Observation 38adb999-42cc-46ce-8d0b-27a8e70069f8 · outbound

This paper cites Time Series Stock Price Forecasting Based on Genetic Algorithm (GA)-Long Short-Term Memory Network (LSTM) Optimization.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Time Series Stock Price Forecasting Based on Genetic Algorithm (GA)-Long Short-Term Memory Network (LSTM) Optimization

Reference 38

Resolution
verified exact
local_arxiv, observed 2026-08-07T04:58:23.359077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:21.069018Z digest=sha256:b3f63b570171970bc6d90a1baa73ec92eea7b9ea11a01aadbde821f007ad9d71

Observation 72d287f0-ff76-4cf2-b841-f07fd964fd99 · outbound

This paper cites Combining evolution and deep reinforcement learning for policy search: A survey.ACM Transactions on Evolutionary Learning, 3(3):1–20, 2023.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Combining evolution and deep reinforcement learning for policy search: A survey.ACM Transactions on Evolutionary Learning, 3(3):1–20, 2023

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:58:25.593148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:21.157243Z digest=sha256:ca5863856486ade7cbf162107bce3f32a8d503ad5bd4d079669b41e9692934a9

Observation 245aba40-78bc-46ad-b5d6-fd6cea58b6d4 · outbound

This paper cites Equity-transformer: Solving np-hard min-max routing problems as sequential generation with equity context.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Equity-transformer: Solving np-hard min-max routing problems as sequential generation with equity context

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:58:25.444540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:21.311974Z digest=sha256:e1955d91dca6cdac521af583730dee42554790bd7149dc8b3ef3d823686c24cc

Observation ae0f6060-82bd-418c-8d10-81be8f845f0f · outbound

This paper cites Learning encodings for constructive neural com- binatorial optimization needs to regret.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Learning encodings for constructive neural com- binatorial optimization needs to regret

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:58:25.260763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:21.451427Z digest=sha256:23f8f93665a5fdf16be3e15e7cd367262f53fbb27f93bab06991f7d8ab1ab894

Observation 09e1f3cc-eed8-434b-9cbc-500900eaca42 · outbound

This paper cites Csrx: A novel crossover operator for a genetic algorithm applied to the traveling salesperson problem.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Csrx: A novel crossover operator for a genetic algorithm applied to the traveling salesperson problem

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:58:25.020829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:21.580167Z digest=sha256:152394154fab28e52c058badd229f4b688f6996e881fd4b1ed7d0c71cd1a7bad

Observation 3e2c418a-f275-4029-b292-8bf7e247f572 · outbound

This paper cites Hybrid genetic search for the cvrp: Open-source implementation and swap* neighborhood.Computers & Operations Research, 140:105643, 2022.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Hybrid genetic search for the cvrp: Open-source implementation and swap* neighborhood.Computers & Operations Research, 140:105643, 2022

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T04:58:21.714204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:58:21.714204Z digest=sha256:e4b571bac37491ad2c0b2893458fe84bd4e680d997698e053028ac39a79b2242

Observation 8c3c30e4-25c5-42ea-922b-f807d1eb7912 · outbound

This paper cites Pointer networks.Advances in neural information processing systems, 28, 2015.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Pointer networks.Advances in neural information processing systems, 28, 2015

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T04:58:21.796697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:58:21.796697Z digest=sha256:d52924c3204f575fb4da5a7eaf39d5e16a5be4fa95e3a12143372c82cbe8c270

Observation 6710beb6-01cd-4a19-94f0-bbb3a7598665 · outbound

This paper cites Leader Reward for POMO-Based Neural Combinatorial Optimization.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Leader Reward for POMO-Based Neural Combinatorial Optimization

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T04:58:21.874424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:58:21.874424Z digest=sha256:1166cfc6401ff5bed86a776fb11ea5b8840ff535f2ea2fb5aec920720becc619

Observation 1406b358-fe33-46e7-b98e-dcadee9f47b6 · outbound

This paper cites Simple statistical gradient-following algorithms for connectionist reinforce- ment learning.Machine learning, 8:229–256, 1992.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Simple statistical gradient-following algorithms for connectionist reinforce- ment learning.Machine learning, 8:229–256, 1992

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T04:58:21.961177Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:58:21.961177Z digest=sha256:e99f0859fbd52e3194a0030a232f391cdfc5871b07d868e518e0e1a0a9e27f6b

Observation c95df7cb-f910-4f2d-841b-13ba3191df8f · outbound

This paper cites Neural Combinatorial Optimization Algorithms for Solving Vehicle Routing Problems: A Comprehensive Survey with Perspectives.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Neural Combinatorial Optimization Algorithms for Solving Vehicle Routing Problems: A Comprehensive Survey with Perspectives

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T04:58:22.079726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:58:22.079726Z digest=sha256:ccc0268e1b5e4fa3e99bc4595aa5fac0960d780e52a9aef29935649ff88522d3

Observation c4ccac05-eabd-4cb6-88b3-6ec0e2a8cb0b · outbound

This paper cites Learning improvement heuristics for solving routing problems.IEEE transactions on neural networks and learning systems, 33(9):5057–5069, 2021.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Learning improvement heuristics for solving routing problems.IEEE transactions on neural networks and learning systems, 33(9):5057–5069, 2021

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:58:24.770164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:22.213260Z digest=sha256:16d31edec20cb22a9155318ec863ff410ae8f1a19d0df7bdebe3183c52132dd3

Observation d5f95264-a82a-416a-89c9-dfc5c4a0b9ba · outbound

This paper cites Optimization of Worker Scheduling at Logistics Depots Using Genetic Algorithms and Simulated Annealing.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization Optimization of Worker Scheduling at Logistics Depots Using Genetic Algorithms and Simulated Annealing

Reference 49

Resolution
verified exact
local_arxiv, observed 2026-08-07T04:58:23.084814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:22.351883Z digest=sha256:94719d8dfc173fe6f887d2e85c9e920e5b0172fe2444e5ab62bdb52df7c5fca9

Observation 8189e4ee-e886-4f2c-9ff5-3084f9072452 · outbound

This paper cites UDC: A Unified Neural Divide-and-Conquer Framework for Large-Scale Combinatorial Optimization Problems.

Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization UDC: A Unified Neural Divide-and-Conquer Framework for Large-Scale Combinatorial Optimization Problems

Reference 50

Resolution
verified exact
local_arxiv, observed 2026-08-07T04:58:22.753264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:58:22.562491Z digest=sha256:11432bdd3394de1656fb14b4ea8cf464d1e64dd46298d2e6df6832abb30b918f

Pith citing papers

No inbound Pith citation observations are available.