  This paper introduces and approximately solves a multi-component problem
where small rectangular items are produced from large rectangular bins via
guillotine cuts. An item is characterized by its width, height, due date, and
earliness and tardiness penalties per unit time. Each item induces a cost that
is proportional to its earliness and tardiness. Items cut from the same bin
form a batch, whose processing and completion times depend on its assigned
items. The items of a batch have the completion time of their bin. The
objective is to find a cutting plan that minimizes the weighted sum of
earliness and tardiness penalties. We address this problem via a constraint
programming based heuristic (CP) and an agent based modelling heuristic (AB).
CP is an impact-based search strategy, implemented in the general-purpose
solver IBM CP Optimizer. AB is constructive. It builds a solution through
repeated negotiations between the set of agents representing the items and the
set representing the bins. The agents cooperate to minimize the weighted
earliness-tardiness penalties. The computational investigation shows that CP
outperforms AB on small-sized instances while the opposite prevails for larger
instances.
