In this paper, we develop a new version of the algorithm proposed in Hi® (Computers and Operations Research 24/8 (1997) 727±736) for solving exactly some variants of (un)weighted constrained twodimensional cutting stock problems. Performance of branch-and-bound procedure depends highly on particular implementation of that algorithm. Programs of this kind are often accelerated drastically by employing sophisticated techniques. In the new version of the algorithm, we start by enhancing the initial lower bound to limit initially the space search. This initial lower bound has already been used in Fayard et al. 1998 (Journal of the Operational Research Society, 49, 1270±1277), as a heuristic for solving the constrained and unconstrained cutting stock problems. Also, we try to improve the upper bound at each internal node of the developed tree, by applying some simple and ecient combinations. Finally, we introduce some new symmetric-strategies used for neglecting some unnecessary duplicate patterns. The performance of our algorithm is evaluated on some problem instances of the literature and other hard-randomly generated problem instances. 7 (M. Hi®). J (NV-pattern but not a NH-pattern) horizontal combination of the patterns A and

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In this paper, we develop a new version of the algorithm proposed in Hifi (Computers and Operations Research 24/8 (1997) 727–736) for solving exactly some variants of (un)weighted constrained two‐dimensional cutting stock problems. Performance of branch‐and‐bound procedure depends highly on particular implementation of that algorithm. Programs of this kind are often accelerated drastically by employing sophisticated techniques. In the new version of the algorithm, we start by enhancing the initial lower bound to limit initially the space search. This initial lower bound has already been used in Fayard et al. 1998 (Journal of the Operational Research Society, 49, 1270–1277), as a heuristic for solving the constrained and unconstrained cutting stock problems. Also, we try to improve the upper bound at each internal node of the developed tree, by applying some simple and effcient combinations. Finally, we introduce some new symmetric‐strategies used for neglecting some unnecessary duplicate patterns. The performance of our algorithm is evaluated on some problem instances of the literature and other hard‐randomly generated problem instances.

The reverse supply chain and disassembly processes are getting more and more important for tackling the burden of waste electrical and electronic equipment. The disassembly's complexity and frequent manual operation makes this process relatively expensive compared to its potential profit. The collection of end-of-life product is also a big issue dealing with vehicle routing. Thus, the decisions taken for collection and disassembly of end-of-life products need to be optimised. In this work, an optimisation model is developed for incorporating these problems. Our experimental study shows joint optimisation of collection and disassembly with coordination between them improves the global performance of the reverse supply chain including lower total cost corresponding to the component demand satisfaction.