Iterative Beam Search for Simple Assembly Line Balancing with a Fixed Number of Work Stations

The simple assembly line balancing problem (SALBP) concerns the assignment of tasks with pre-defined processing times to work stations that are arranged in a line. Hereby, precedence constraints between the tasks must be respected. The optimization goal of the SALBP-2 version of the problem concerns the minimization of the so-called cycle time, that is, the time in which the tasks of each work station must be completed. In this work we propose to tackle this problem with an iterative search method based on beam search. The proposed algorithm is able to obtain optimal, respectively best-known, solutions in 283 out of 302 test cases. Moreover, for 9 further test cases the algorithm is able to produce new best-known solutions. These numbers indicate that the proposed iterative beam search algorithm is currently a state-of-the-art method for the SALBP-2

Exact and heuristic methods for solving the Robotic Assembly Line Balancing Problem

[EN] In robotic assembly lines, the task times depend on the robots assigned to each station. Robots are considered an unlimited resource and multiple robots of the same type can be assigned to different stations. Thus, the Robotic Assembly Line Balancing Problem (RALBP) consists of assigning a set of tasks and a type of robot to each station, subject to precedence constraints between the tasks. This paper proposes a lower bound, and exact and heuristic algorithms for the RALBP. The lower bound uses chain decomposition to explore the graph dependencies. The exact approaches include a novel linear mixed-integer programming model and a branch-bound-and-remember algorithm with problem-specific dominance rules. The heuristic solution is an iterative beam search with the same rules. To fully explore the different characteristics of the problem, we also propose a new set of instances. The methods and algorithms are extensively tested in computational experiments showing that they are competitive with the current state of the art. (C) 2018 Elsevier B.V. All rights reserved.Borba, L.; Ritt, M.; Miralles Insa, CJ. (2018). Exact and heuristic methods for solving the Robotic Assembly Line Balancing Problem. European Journal of Operational Research. 270(1):146-156. https://doi.org/10.1016/j.ejor.2018.03.011S146156270

Heuristics and Lower Bounds for the Simple Assembly Line Balancing Problem Type 1: Overview, Computational Tests and Improvements

Assigning tasks to work stations is an essential problem which needs to be addressed in an assembly line design. The most basic model is called simple assembly line balancing problem type 1 (SALBP-1). We provide a survey on 12 heuristics and 9 lower bounds for this model and test them on a traditional and a lately-published benchmark dataset. The present paper focuses on algorithms published before 2011. We improve an already existing dynamic programming and a tabu search approach significantly. These two are also identified as the most effective heuristics; each with advantages for certain problem characteristics. Additionally we show that lower bounds for SALBP-1 can be distinctly sharpened when merging them and applying problem reduction techniques

Re-balancing problem for assembly lines: new mathematical model and exact solution method

The purpose of this study is to develop a new mathematical model and an exact solution method for an assembly line rebalancing problem. When an existing assembly line has to be adapted to a new production context, the line balancing, resources allocation and component management solutions have to be revised. The objective is to minimize the number of modifications to be done in the initial line in order to reduce the time and investment needed to meet new production requirements. The proposed model is evaluated via a computational experiment. The obtained results the efficacy of the proposed method

Research Trends and Outlooks in Assembly Line Balancing Problems

This paper presents the findings from the survey of articles published on the assembly line balancing problems (ALBPs) during 2014-2018. Before proceeding a comprehensive literature review, the ineffectiveness of the previous ALBP classification structures is discussed and a new classification scheme based on the layout configurations of assembly lines is subsequently proposed. The research trend in each layout of assembly lines is highlighted through the graphical presentations. The challenges in the ALBPs are also pinpointed as a technical guideline for future research works

Time and space multi-manned assembly line balancing problem using genetic algorithm

Purpose: Time and Space assembly line balancing problem (TSALBP) is the problem of balancing the line taking the area required by the task and to store the tools into consideration. This area is important to be considered to minimize unplanned traveling distance by the workers and consequently unplanned time waste. Although TSALBP is a realistic problem that express the real-life situation, and it became more practical to consider multi-manned assembly line to get better space utilization, few literatures addressed the problem of time and space in simple assembly line and only one in multi-manned assembly line. In this paper the problem of balancing bi-objective time and space multi-manned assembly line is proposed Design/methodology/approach: Hybrid genetic algorithm under time and space constraints besides assembly line conventional constraints is used to model this problem. The initial population is generated based on conventional assembly line heuristic added to random generations. The objective of this model is to minimize number of workers and number of stations. Findings: The results showed the effectiveness of the proposed model in solving multi-manned time and space assembly line problem. The proposed method gets better results in solving real-life Nissan problem compared to the literature. It is also found that there is a relationship between the variability of task time, maximum task time and cycle time on the solution of the problem. In some problem features it is more appropriate to solve the problem as simple assembly line than multi-manned assembly line. Originality/value: It is the first article to solve the problem of balancing multi-manned assembly line under time and area constraint using genetic algorithm. A relationship between the problem features and the solution is found according to it, the solution method (one sided or multi-manned) is definedPeer Reviewe