Pith Number

pith:RIUKTZYT

pith:2026:RIUKTZYT77U5SJ4XOXHPLKPCVV

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Adaptive mine planning under geological uncertainty: A POMDP framework for sequential decision-making

Abdellatif Elghali, Hamza Khalifi, Jef Caers, Mostafa Benzaazoua, Yassine Taha

Mine scheduling as a POMDP produces adaptive policies that shrink the expectation-reality gap from 22.3% to 4.6% and raise realized NPV by up to USD44.6M under prior error.

arxiv:2605.13702 v1 · 2026-05-13 · cs.AI

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Claims

C1strongest claim

Under a statistically consistent prior, the SA-POMDP reduces the expectation-reality gap from 22.3% to 4.6%, improving realized NPV by USD8.4M relative to one-shot stochastic optimization. Under systematic prior misspecification of 10%, the adaptive framework outperforms static planning by up to USD44.6M (36.9%).

C2weakest assumption

That the hybrid SA-POMDP architecture (simulated annealing value approximation plus ES-MDA belief updates) yields a policy whose expected value under the true (unknown) geology is accurately estimated without material approximation bias or computational artifacts.

C3one line summary

A hybrid SA-POMDP framework for adaptive mine planning under geological uncertainty reduces the expectation-reality gap from 22.3% to 4.6% and improves realized NPV by up to USD44.6M compared with conventional one-shot stochastic optimization.

References

16 extracted · 16 resolved · 0 Pith anchors

[1] Simultaneous stochastic optimization of production sequence and dynamic cut -off grades in an open pit mining operation 2020 · doi:10.1016/j.resourpol.2020.101634

[2] Global optimization of open pit mining complexes with uncertainty 2016 · doi:10.1016/j.asoc.2015.11.038

[3] Simultaneous stochastic optimization of mining complexes - mineral value chains: an overview of concepts, examples and comparisons 2022 · doi:10.1080/17480930.2022.2065730

[4] Production scheduling with uncertain supply: A new solution to the open pit mining problem 2013 · doi:10.1007/s11081-012-

[5] Adaptive open -pit mining planning under geological uncertainty 2021 · doi:10.1016/j.resourpol.2021.102086

Receipt and verification

First computed	2026-05-18T02:44:16.839290Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

8a28a9e713ffe9d9279775cef5a9e2ad6fbaa3919261f976f46f94b91fb16dd4

Aliases

arxiv: 2605.13702 · arxiv_version: 2605.13702v1 · doi: 10.48550/arxiv.2605.13702 · pith_short_12: RIUKTZYT77U5 · pith_short_16: RIUKTZYT77U5SJ4X · pith_short_8: RIUKTZYT

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/RIUKTZYT77U5SJ4XOXHPLKPCVV \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 8a28a9e713ffe9d9279775cef5a9e2ad6fbaa3919261f976f46f94b91fb16dd4

Canonical record JSON

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    "abstract_canon_sha256": "c7af33879909397dddc9d74752dcd461cf25024d557f275210287b33cf721ad3",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.AI",
    "submitted_at": "2026-05-13T15:52:29Z",
    "title_canon_sha256": "4f5dbbe64db45efa6853d24057e4b1f9c63dfda7fee6ef83926ea84395fa67f2"
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    "kind": "arxiv",
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