A comparison of formulations for the simple assembly line balancing problem (original) (raw)
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An improved mathematical program to solve the simple assembly line balancing problem
International Journal of Production Research, 2009
The Simple Assembly Line Balancing Problem (SALBP) has been extensively examined in the literature. Various mathematical programs have been developed to solve SALBP type-1 (minimizing the number of workstations, m , for a given cycle time, ct) and SALBP type-2 (minimizing ct given m). Usually, an initial pre-process is carried out to calculate the range of workstations to which a task i may be assigned, in order to reduce the number of variables of task-workstation assignment. This paper presents a more effective mathematical program than those released to date to solve SALBP-1 and SALBP-2. The key idea is to introduce additional constraints in the mathematical program, based on the fact that the range of workstations to which a task i may be assigned depends either on the upper bound on the number of workstations or on the upper bound on the cycle time (for SALBP-1 and SALBP-2, respectively). A computational experiment was carried out and the results reveal the superiority of the mathematical program proposed.
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.
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.
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.
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.
An enumerative heuristic and reduction methods for the assembly line balancing problem
European Journal of Operational Research, 2003
A new heuristic algorithm and new reduction techniques for the type 1 assembly line balancing problem are presented. The new heuristic is based on the well-known Hoffmann heuristic and builds solutions from both sides of the precedence network to choose the best. The reduction techniques aim at augmenting precedences, conjoining tasks and increasing operation times. The heuristic is tested on its own and also in combination with the reduction techniques. The tests, which are carried out on a well-known benchmark set of problem ...
Journal of Manufacturing Systems, 2019
The scope of the assembly line balancing problem in research is clear, with well-defined sets of assumptions, parameters, and objective functions. In application, these borders are frequently transgressed. Many of these deviations are internal to the assembly line balancing problem itself, arising from any of the physical or technological features in modern assembly lines. Other issues are founded in the tight coupling of assembly line balancing with external production planning and management problems, as assembly lines are at the intersection of multiple related problems in job sequencing, part flow logistics, worker safety, and quality. General assembly line balancing is devoted to studying the solution techniques necessary to model these applied line balancing problems. This article presents a complex line balancing problem based on the real production environment of our industrial partner, featuring several extensions for task-to-task relationships, station characteristics limiting assignment, and parallel worker zoning interactions. A heuristic, combining rank-position-weighting, last-fitimprovement and iterative blocking scheme, and an integer program that can manage multiple constraint types simultaneously, are developed. An experiment is conducted testing each of these new solution methods upon a battery of testbed problems, measuring solution quality, runtime, and achievement of feasibility. Results indicate that the integer programming model provides a viable solution method for those industries with access to commercial solvers.
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.