Highlights Novel MINLP model for multi-floor, cross-dock door assignment problem. A general-purpose nonlinear programming solution framework. Multi-start, genetic random-key, and very-large-scale neighborhood search as the diversification strategies. Very-large sized instances with size of cost matrix up to 90,000 by 90,000.
Abstract This paper is concerned with the multi-floor, cross-dock door assignment problem (MCDAP) to minimize the total material handling costs. We present a novel mixed-integer nonlinear programming model and a classic linearization form for the MCDAP. We use a combination of multi-start, genetic random-key, and very-large-scale neighborhood search (VLSN) as the diversification strategies for the solution perturbation method embedded within the critical event Tabu search to solve MCDAP. We will test the proposed algorithms on a set of 60 very-large sized instances with 150–300 loading doors, and 100–300 unloading doors that raise size of cost matrix up to 90,000 by 90,000.
The multi-floor cross-dock door assignment problem: Rising challenges for the new trend in logistics industry
2019-10-25
18 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Natural Optimization Algorithms for the Cross-Dock Door Assignment Problem
Online Contents | 2016
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