Tightening concise linear reformulations of 0-1 cubic programs

Integrating storage location and order picking problems in warehouse planning

“…We also highlight how fast the average time to prove optimality increases by adding more slots to the warehouse, even with only three picks. In larger instances, the SLOPP model runs out of memory, which is in line with Forrester [13] about the standard linearization technique requiring a huge number of variables and constraints. The linearization of the cubic term in the objective function in the SLOPP model requires the introduction of O(|O||L| 2 |P 2 |) new variables and constraints, which for large instances of the small set represents hundreds of millions of new variables.…”