Abstract
Alternative material flow strategies in logistics networks have crucial influences on the overall performance of the networks. Material flows can follow push, pull, or hybrid systems. To get the advantages of both push and pull flows in networks, the decoupling-point strategy is used as coordination mean. At this point, material pull has to get optimized concerning customer orders against pushed replenishment-rates. To compensate the ambiguity and uncertainty of both dynamic flows, fuzzy set theory can practically be applied. This paper has conceptual and mathematical parts to explain the performance of the push-pull flow strategy in a supply network and to give a novel solution for optimizing the pull side employing Conwip system. Alternative numbers of pallets and their lot-sizes circulating in the assembly system are getting optimized in accordance with a multi-objective problem; employing a hybrid approach out of meta-heuristics (genetic algorithm and simulated annealing) and fuzzy system. Two main fuzzy sets as triangular and trapezoidal are applied in this technique for estimating ill-defined waiting times. The configured technique leads to smoother flows between push and pull sides in complex networks. A discrete-event simulation model is developed to analyze this thesis in an exemplary logistics network with dynamics.
Highlights
Today, after spanning the extension phase from simple companies towards supply chains and correlated networks, more complex logistics processes have been burdened to industries [1]
The current study is a part of a greater research project which proceeds with material flow control throughout supply networks, this paper only focuses on the pull section of hybrid system and tries to optimize the number of carrier carts and their lot sizes for smoother flows
simulated annealing (SA) performs according to the lowenergy state principle in aligning metal atoms, which is dependent on gradually cooling the temperature in annealing process similar to thermodynamics
Summary
After spanning the extension phase from simple companies towards supply chains and correlated networks, more complex logistics processes have been burdened to industries [1]. The current study is a part of a greater research project which proceeds with material flow control throughout supply networks, this paper only focuses on the pull section of hybrid system and tries to optimize the number of carrier carts (pallet) and their lot sizes for smoother flows For this purpose, a discrete-event simulation scenario of a hybrid logistics network is developed facing dynamics in their processes (material replenishments and demands). The main contributions are to show the privileges of fuzzy control system for smoothing the flow of distributed pallets, the contribution of heuristics in approximating the optimum combination values of just some key factors of pull flows in a logistics networks, for example, number of carts, and flexible lot sizes, and the simplicity and applicability of fuzzy set theory in solving multiobjective problems by means of defining satisfaction degrees.
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