A New Multi-Objective Genetic Algorithm for Assembly Line Balancing

نویسندگان

چکیده

Abstract The aim of this work is to enable a step towards self-adapting digital toolset for manufacturing planning focusing on minimally constrained assembly line balancing. approach includes the simultaneous definition optimum number workstations, cycle time and assignment tasks workstations. A bespoke genetic algorithm (GENALSAS) proposed demonstrated which focuses examining simple balancing problem (SALBP). (GA) has been shown consistently deliver detailed production plans SALBP forms with minimum inputs. Neither workstations nor system assumed/fixed as in previous field. simultaneously attains better performing solutions compared studies both terms converge quality solution.

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Multi-Objective Particle Swarm Optimization for Mixed-Model Assembly Line Balancing with Different Skilled Workers

This paper presents a multi-objective Particle Swarm Optimization (PSO) algorithm for worker assignment and mixed-model assembly line balancing problem when task times depend on the worker’s skill level. The objectives of this model are minimization of the number of stations (equivalent to the maximization of the weighted line efficiency), minimization of the weighted smoothness index and minim...

متن کامل

A multi-objective genetic algorithm for a mixed-model assembly U-line balancing type-I problem considering human-related issues, training, and learning

Mixed-model assembly lines are increasingly accepted in many industrial environments to meet the growing trend of greater product variability, diversification of customer demands, and shorter life cycles. In this research, a new mathematical model is presented considering balancing a mixed-model U-line and human-related issues, simultaneously. The objective function consists of two separate com...

متن کامل

A Multi-Objective Genetic Algorithm for Solving Assembly Line Balancing Problem

In this paper, a multi-objective genetic agorithm to solve assembly line balancing problems is proposed. The performance criteria considered are the number of workstations, the line efficiency, the smoothness index before trade and transfer, and the smoothness index after trade and transfer. The developed genetic algorithm is compared with six popular heuristic algorithms, namely, ranked positi...

متن کامل

Multi-objective fuzzy assembly line balancing using genetic algorithms

This paper presents a fuzzy extension of the simple assembly line balancing problem of type 2 (SALBP-2) with fuzzy job processing times since uncertainty, variability, and imprecision are often occurred in real-world production systems. The jobs processing times are formulated by triangular fuzzy membership functions. The total fuzzy cost function is formulated as the weighted-sum of two bi-cri...

متن کامل

A multi-objective genetic algorithm (MOGA) for hybrid flow shop scheduling problem with assembly operation

Scheduling for a two-stage production system is one of the most common problems in production management. In this production system, a number of products are produced and each product is assembled from a set of parts. The parts are produced in the first stage that is a fabrication stage and then they are assembled in the second stage that usually is an assembly stage. In this article, the first...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Journal of Computing and Information Science in Engineering

سال: 2022

ISSN: ['1530-9827', '1944-7078']

DOI: https://doi.org/10.1115/1.4055426