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Mohammed Lagmah

Publications and source records attributed to Mohammed Lagmah.

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Bucket Brigades: Uniqueness of the Fixed Point and Three-Worker Asymptotics

A standard organization of production lines exhibiting self-balancing behavior is given by bucket brigades. Their study in operations research was initiated by the foundational work of Bartholdi and Eisenstein ({\em Operations Research}, 1996), where a simplified version of the model is considered. Their main result shows that when workers are ordered from the slowest to the fastest, the system is stable and converges to a ``fixed point,'' where each worker oscillates between two limiting positions. They also observe that the dynamics can become highly complex when this ordering condition is not satisfied. The {\em no-station} setting, in which work is distributed continuously and uniformly along the production line, is given special attention in their work. In a subsequent paper with Bunimovich ({\em Operations Research}, 1999), they characterize all stable behaviors of this setting for up to three workers. In this work, we extend their analysis for three workers beyond the stable regime, providing a complete description when workers are ordered from the fastest to the slowest. We also show that, due to their restrictive notion of stability, some of their conclusions must be revisited. Finally, for an arbitrary number of workers, we prove that the fixed point is always unique in the no-station setting.

math.DS

Proven Approximation Guarantees in Multi-Objective Optimization: SPEA2 Beats NSGA-II

Together with the NSGA-II and SMS-EMOA, the strength Pareto evolutionary algorithm 2 (SPEA2) is one of the most prominent dominance-based multi-objective evolutionary algorithms (MOEAs). Different from the NSGA-II, it does not employ the crowding distance (essentially the distance to neighboring solutions) to compare pairwise non-dominating solutions but a complex system of $σ$-distances that builds on the distances to all other solutions. In this work, we give a first mathematical proof showing that this more complex system of distances can be superior. More specifically, we prove that a simple steady-state SPEA2 can compute optimal approximations of the Pareto front of the OneMinMax benchmark in polynomial time. The best proven guarantee for a comparable variant of the NSGA-II only assures approximation ratios of roughly a factor of two, and both mathematical analyses and experiments indicate that optimal approximations are not found efficiently.

cs.NE