SALOME: A Bidirectional Branch-and-Bound Procedure for Assembly Line Balancing

Abstract

In this article, we report on new results for the well-known Simple Assembly Line Balancing Problem Type 1. For this NP-hard problem, a large number of exact and heuristic algorithms have been proposed in the last four decades. Recent research has led to efficient branch-and-bound procedures. Based on an analysis of their specific strengths, a new algorithm (Salome) is developed. Its main characteristic is a new branching strategy (local lower-bound method) and a bidirectional branching rule. Furthermore, new bounding and dominance rules are included. Computational experiments on the basis of former data sets, as well as a new, more challenging one, show that Salome outperforms the most effective existing procedures for solving this problem.

Yasak Arama Algori̇tmasina Dayali Pürüzsüzleşti̇rme Yaklaşimi İçeren Karişik-Modelli̇ Montaj Hatti Dengeleme

“…burada m T , m modelinin bir istasyon başına düşen dönemsel ortalamalı işlem süresi aşağıdaki gibi belirlenir: Algoritmanın performansı, Genetik Algoritma (GA) metasezgiseli ve Scholl ve Klein [54] tarafından geliştirilen SALOME dal-sınır algoritması ile karşılaştırılmıştır. GA, montaj hattı dengeleme gibi birleşimsel optimizasyon problemlerinin çözümünde çok yaygın olarak kullanılmış ve başarılı sonuçlar elde edilmiştir [55,56,57,58].…”

Optimally solving the alternative subgraphs assembly line balancing problem

“…As solution method for solving the included SALBP instances, we apply the branch-and-bound procedure SALOME of Scholl and Klein (1997) which is supposably the best exact solution method available for SALBP (cf. Sprecher 1999; Scholl andKlein 1999, Scholl 1999).…”

Beam-ACO Applied to Assembly Line Balancing

“…Solution approaches include constructive heuristics based on priority rules (see [20]), enumerative procedures such as branch & bound approaches (see [10,9,15,19]), and several metaheuristics such as tabu search [16,11], simulated annealing [21], evolutionary computation [8], and ant colony optmization [2,3]. The current situation for the SALBP-1 problem is quite unusual: Enumerative approaches such as SALOME [15] still appear to be at least as successful as metaheuristic approaches. However, the interest in well-working metaheuristics is high, because the applicability of enumerative methods is limited to academic formulations of the problem, and even slight differences between a real problem and the academic SALBP-1 make an enumerative approach unapplicable.…”