Solving Assembly Line Balancing Problems by Combining IP and CP

Assembly line balancing problems consist in partitioning the work necessary to assemble a number of products among different stations of an assembly line. We present a hybrid approach for solving such problems, which combines constraint programming and integer programming.Comment: 10 pages, Sixth Annual Workshop of the ERCIM Working Group on Constraints, Prague, June 200

The influence of line balancing on line feeding for mixed-model assembly lines

Though, recent research on mixed-model Assembly Line Balancing Problems (MALBP) and Assembly Line Feeding Problems (ALFP) aims to incorporate real-world aspects, research on the integration of both areas is still limited. This paper helps closing this gap by studying the influence of different balancing objectives on line feeding decisions and costs. For line balancing, different objective functions were formulated and the results were used as input when solving the ALFP. Although, no large cost differences were found, we observed that decision making in line feeding does depend on the balance

A STUDY ON GENERAL ASSEMBLY LINE BALANCING MODELING METHODS AND TECHNIQUES

The borders of the assembly line balancing problem, as classically drawn, are as clear as any other operations research topic in production planning, with well-defined sets of assumptions, parameters, and objective functions. In application, however, these borders are frequently transgressed. Many of these deviations are internal to the assembly line balancing problem itself, arising from any of a wide array of 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. The field of General Assembly Line Balancing is devoted to studying the class of adapted and extended solution techniques necessary in order to model these applied line balancing problems. In this dissertation a complex line balancing problem is presented 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 constructive heuristic is developed along with two improvement heuristics, as well as an integer programming model for the same problem. 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. Additionally, a new method for measuring a secondary horizontal line balancing objective is established, based on the options-mix paradigm rather than the customary model-mix paradigm

SALBPGen - A systematic data generator for (simple) assembly line balancing

Assembly line balancing is a well-known and extensively researched decision problem which arises when assembly line production systems are designed and operated. A large variety of real-world problem variations and elaborate solution methods were developed and presented in the academic literature in the past 60 years. Nevertheless, computational experiments examining and comparing the performance of solution procedures were mostly based on very limited data sets unsystematically collected from the literature and from some real-world cases. In particular, the precedence graphs used as the basis of former tests are limited in number and characteristics. As a consequence, former performance analyses suffer from a lack of systematics and statistical evidence. In this article, we propose SALPBGen, a new instance generator for the simple assembly line balancing problem (SALBP) which can be applied to any other assembly line balancing problem, too. It is able to systematically create instances with very diverse structures under full control of the experiment's designer. In particular, based on our analysis of real-world problems from automotive and related industries, typical substructures of the precedence graph like chains, bottlenecks and modules can be generated and combined as required based on a detailed analysis of graph structures and structure measures like the order strength. We also present a collection of new challenging benchmark data sets which are suited for comprehensive statistical tests in comparative studies of solution methods for SALBP and generalized problems as well. Researchers are invited to participate in a challenge to solve these new problem instances.manufacturing, benchmark data set, assembly line balancing, precedence graph, structure analysis, complexity measures

Robust optimization for U-shaped assembly line worker assignment and balancing problem with uncertain task times

Awareness of the importance of U-shaped assembly line balancing problems is all on the rise. In the U-shaped assembly line, balancing is affected by the uncertainty associated with the assembly task times. Therefore, it is crucial to develop an approach to respond to the uncertainty caused by the task times. When the great majority of existing literature related to uncertainty in the assembly line is considered, it is observed that the U-shaped assembly line balancing problem under uncertainty is scarcely investigated. That being the case, we aim to fill this research gap by proposing a robust counterpart formulation for the addressed problem. In this study, a robust optimization model is developed for the U-shaped assembly line worker assignment and balancing problem (UALWABP) to cope with the task time uncertainty characterized by a combined interval and polyhedral uncertainty set. A real case study is conducted through data from a company producing water meters

A mixed-integer programming model for cycle time minimization in assembly line balancing: Using rework stations for performing parallel tasks

[EN] In assembly lines, rework stations are generally used for reprocessing defective items. On the other hand, using rework stations for this purpose only might cause inefficient usage of the resources in this station especially in an assembly line with a low defective rate. In this study, a mixed-integer programming model for cycle time minimization is proposed by considering the use of rework stations for performing parallel tasks. By linearizing the non-linear constraint about parallel tasks using a variate transformation, the model is transformed to a linear-mixed-integer form. In addition to different defective rates, different rework station positions are also considered using the proposed model. The performance of the model is analyzed on several test problems from the related literature.Cavdur, F.; Kaymaz, E. (2020). A mixed-integer programming model for cycle time minimization in assembly line balancing: Using rework stations for performing parallel tasks. 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A tabu search approach for mixed-model parallel assembly line balancing problem (type II)

There are two types of assembly line balancing problems (ALBPs), which have received a great attention in the literature during the past four decades: types I and II. Both versions of ALBP are NP-hard and cannot be solved by exact methods. This paper presents an efficient tabu search (TS) metaheuristic approach for allocating tasks to balance the mixed-model production through the parallel assembly lines. Firstly, an initial solution is determined by a heuristic algorithm. Secondly, an optimum cycle time for each line in the mixed-model parallel assembly line (MMPAL) is calculated through the TS. The developed methodology, tabu search mixed-model parallel assembly line balancing (TMMPALB) model, is tested on test problems producing three and four products. Computational experiments show that the TMMPALB produces good enough solutions in case of MMPALs. The results of the proposed procedure improve cycle times of 77 test problems out of 87

Profit-oriented disassembly-line balancing

As product and material recovery has gained importance, disassembly volumes have increased, justifying construction of disassembly lines similar to assembly lines. Recent research on disassembly lines has focused on complete disassembly. Unlike assembly, the current industry practice involves partial disassembly with profit-maximization or cost-minimization objectives. Another difference between assembly and disassembly is that disassembly involves additional precedence relations among tasks due to processing alternatives or physical restrictions. In this study, we define and solve the profit-oriented partial disassembly-line balancing problem. We first characterize different types of precedence relations in disassembly and propose a new representation scheme that encompasses all these types. We then develop the first mixed integer programming formulation for the partial disassembly-line balancing problem, which simultaneously determines (1) the parts whose demand is to be fulfilled to generate revenue, (2) the tasks that will release the selected parts under task and station costs, (3) the number of stations that will be opened, (4) the cycle time, and (5) the balance of the disassembly line, i.e. the feasible assignment of selected tasks to stations such that various types of precedence relations are satisfied. We propose a lower and upper-bounding scheme based on linear programming relaxation of the formulation. Computational results show that our approach provides near optimal solutions for small problems and is capable of solving larger problems with up to 320 disassembly tasks in reasonable time