An improved mathematical program to solve the simple assembly line balancing problem (original) (raw)
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Heuristic procedures for solving the general assembly line balancing problem with setups
International Journal of Production Research, 2010
The General Assembly Line Balancing Problem with Setups (GALBPS) was recently defined in the literature. It adds sequence-dependent setup time considerations to the classical Simple Assembly Line Balancing Problem (SALBP) as follows: whenever a task is assigned next to another at the same workstation, a setup time must be added to compute the global workstation time, thereby providing the task sequence inside each workstation. This paper proposes over 50 priority-rule-based heuristic procedures to solve GALBPS, many of which are an improvement upon heuristic procedures published to date.
A comparison of formulations for the simple assembly line balancing problem
2011
Abstract: Assembly line balancing is a well-known problem in operations research. It consists in finding an assignment of tasks to some arrangement of stations where the tasks are executed. Typical objective functions require to minimize the cycle time for a given number of stations or the number of stations for a given cycle time.
Literature review of assembly line balancing problems
The International Journal of Advanced Manufacturing Technology, 2014
Mass production system design is a key for the productivity of an organization. Mass production system can be classified into production line machining a component and production line assembling a product. In this paper, the production line assembling a product, which is alternatively called as assembly line system, is considered. In this system, balancing the assembly line as per a desired volume of production per shift is a challenging task. The main objectives of the assembly line design are to minimize the number of workstations for a given cycle time (type 1), to minimize the maximum of the times of workstations for a given number of workstations (type 2), and so forth. Because this problem comes under combinatorial category, the use of heuristics is inevitable. Development of a mathematical model may also be attempted, which will help researchers to compare the solutions of the heuristics with that of the model. In this paper, an attempt is made to present a comprehensive review of literature on the assembly line balancing. The assembly line balancing problems are classified into eight types based on three parameters, viz. the number of models (single-model and multi-model), the nature of task times (deterministic and probabilistic), and the type of assembly line (straight-type and U-type). The review of literature is organized as per the above classification. Further, directions for future research are also presented.
Comparative Analysis of Different Heuristics for Cost Oriented Assembly Line Balancing Problems
Abstract— Assembly line balancing problem consists of a finite set of tasks, where each of them has a duration time and precedence relations, which specify the acceptable ordering of the tasks. Line balancing is an attempt to locate tasks to each workstation on the assembly line. The basic ALB problem is to assign a set of tasks to an ordered set of workstations, so that the precedence relationships were satisfied, and performance factors were optimized. This paper shows the comparison of different heuristics for cost oriented assembly line balancing problem which has been taken from literature. Comparison is done on the basis of their smoothness index, cost and line efficiency. The computational results show that the proposed heuristic performs better and minimizes the production cost.
Journal of Manufacturing Systems, 2014
This paper is the first one of the two papers entitled "modeling and solving mixed-model assembly line balancing problem with setups", which has the aim of developing the mathematical programming formulation of the problem and solving it with a hybrid meta-heuristic approach. In this current part, a mixed-integer linear mathematical programming (MILP) model for mixed-model assembly line balancing problem with setups is developed. The proposed MILP model considers some particular features of the real world problems such as parallel workstations, zoning constraints, and sequence dependent setup times between tasks, which is an actual framework in assembly line balancing problems. The main endeavor of Part-I is to formulate the sequence dependent setup times between tasks in type-I mixed-model assembly line balancing problem. The proposed model considers the setups between the tasks of the same model and the setups because of the model switches in any workstation. The capability of our MILP is tested through a set of computational experiments. Part-II tackles the problem with a multiple colony hybrid bees algorithm. A set of computational experiments is also carried out for the proposed approach in Part-II.
Assembly Automation, 2009
Patterson and Albracht [1] formulated a binary integer programming model for the simple assembly line balancing problem, which is well known as SALBP-1, in more than 30 years ago. Since then, a number of researchers have extended the model for the variants of assembly line balancing problem. The model is still prevalent nowadays mainly because of the lower and upper bounds on task assignment. These properties avoid significant increase of decision variables. In this paper we use an example to show that the model may lead to a confusing solution. We then provide a "remedial" constraint set for the model to rectify the disordered sequence problem.
Optimization of Cycle Time in an Assembly Line Balancing Problem
Procedia Technology, 2016
Assembly line is a sequential work flow production systems which are still typical in the mass production of standard products. In mixed model assembly line system, it can produce the production sequentially by mixing more than one product on the same line. Different range of products are produced on the same line are quiet similar to the main product This paper proposes an approach to the mixed model assembly line balancing problem (MALBP) with parallel workstations. Different methods are developed to solve assembly line balancing problems. The existing methods to solve assembly line balancing problem cannot be applied to combinatorial type problems. When we use heuristics methods for a combinatorial type problem which has more number of work elements, it may not give an optimal solution and become tedious. So this paper is aimed to propose a method to solve such type of complex line balancing problems.
MODELING OF ASSEMBLY LINE BALANCING FOR OPTIMIZED NUMBER OF STATIONS AND TIME
iaeme
In this work, the Buxey 29 tasks problem is solved for minimum number of stations and cycle time. The precedence matrix is presented for the 29 tasks. The classification of ALB problem and their solution procedure are presented. Single model ALB and equivalent multi model ALB are treated as similar model and common solution procedure is presented. The number of stations required for the feasible solutions are varied and cycle time are computed. The algorithm used in the derivation of the feasible solutions is presented. The advantages of using a certain number of stations are discussed. Finally important conclusions are drawn and future work is defined.
Modelling and optimisation of assembly line balancing problem with resource constraint
2019
Assembly Line Balancing (ALB) is about distributing the assembly tasks into workstations with the almost equal workload. Previous research mostly assumed that all workstations are having similar capabilities including the machines, tools and worker skills. Recently, researchers started to consider the resource constraints in ALB such as machine and worker. Optimisation of ALB with resource constraints gives a huge benefit to the industry such as increase line efficiency, optimise the resources utilisation and can reduce production cost. This research presents Assembly Line Balancing with resource constraints (ALB-RC) for a simple model with the objectives to minimise the workstation, machine and worker. For the optimisation purpose, this research introduces Genetic Algorithm (GA) with two new crossovers. The crossovers are developed using a ranking approach and known as rank-based crossover type I and type II (RBC-I and RBC-II). The GA with new crossover is tested against popular combinatorial crossovers with a wide range of problem difficulties consisting of 17 benchmark problems. The performance of the proposed GA with new crossover in optimisation ALB-RC is finally validated using an industrial case study. The computational experiment results indicated that the proposed GA with new crossovers are able to find the optimal solution for ALB-RC better than popular combinatorial crossovers. Meanwhile, the results of industrial case study validated that the proposed ALB-RC model is capable to be used for the real industrial problem. At the same time, the result indicated that the GA with rank-based crossover is capable to optimise real-life problem. As a comparison, the number of workstation, machine/tools and workers had reduced between 10-15% for the optimised layout using GA with RBC, compared with the original layout in the case study problem. v