What does this research mean for the field?

The parallel stack loading problem is polynomially solvable when stack capacity is unlimited, and two exact approaches are proposed for the finite-capacity case. Novelty: ClaimNovelty.NOVEL_FINDING. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

The research aims to solve the parallel stack loading problem while minimizing badly-placed items.

March 14, 2026European Journal of Operational ResearchOpen Access

The Parallel Stack Loading Problem: Polynomial Solvability in the Unlimited-Capacity Case and Exact Approaches for the Finite-Capacity Case

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Authors

STShunji Tanaka SBSven Boge SKSigrid Knust

Discussion

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Overview

Analysis reveals polynomial solvability and effective exact approaches for loading items in warehouses, implying improved logistics.

Key Points

The research aims to solve the parallel stack loading problem while minimizing badly-placed items.
Proved polynomial solvability with unlimited stack capacity.
Developed valid inequalities for integer programming formulation.
Created a branch-and-cut algorithm for finite capacity.
Implemented a combinatorial Benders decomposition algorithm.
Conducted numerical experiments to assess the approaches.
Established polynomial solvability under unlimited stack capacity.
Improved integer programming formulation with valid inequalities.
Demonstrated effectiveness of exact approaches through comprehensive experiments.

Cite This Study

Tanaka et al. (2026) studied this question.

synapsesocial.com/papers/69b4fac6b39f7826a300b613 https://doi.org/10.1016/j.ejor.2026.03.009

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March 14, 2026European Journal of Operational ResearchOpen Access

The Parallel Stack Loading Problem: Polynomial Solvability in the Unlimited-Capacity Case and Exact Approaches for the Finite-Capacity Case

View Full Paper

Ask AI

Bookmark

Authors

STShunji Tanaka SBSven Boge SKSigrid Knust

Discussion

Member takes

Overview

Analysis reveals polynomial solvability and effective exact approaches for loading items in warehouses, implying improved logistics.

Key Points

The research aims to solve the parallel stack loading problem while minimizing badly-placed items.
Proved polynomial solvability with unlimited stack capacity.
Developed valid inequalities for integer programming formulation.
Created a branch-and-cut algorithm for finite capacity.
Implemented a combinatorial Benders decomposition algorithm.
Conducted numerical experiments to assess the approaches.
Established polynomial solvability under unlimited stack capacity.
Improved integer programming formulation with valid inequalities.
Demonstrated effectiveness of exact approaches through comprehensive experiments.

Cite This Study

Tanaka et al. (2026) studied this question.

synapsesocial.com/papers/69b4fac6b39f7826a300b613 https://doi.org/10.1016/j.ejor.2026.03.009

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