A special case of transfer lines balancing by graph approach

A balancing problem for paced production lines with workstations in series and blocks of parallel operations at the workstations is considered. Operations of each workstation are partitioned into blocks. All operations of the same block are performed simultaneously by one spindle head. All blocks of the same workstation are also executed simultaneously. The relations of the necessity of executing some operations at the same workstation, the possibility of combining the blocks at the same workstation as well as precedence constraints are given. The operation time of the workstation is the maximal value among operation times of its blocks. The line cycle time is the maximal workstation time. The problem is to choose blocks from a given set and allocate them to workstations in such a way that (i) all the operations are assigned, (ii) the above constraints are satisfied, (iii) a given cycle time is not exceeded, and (iv) the line cost is minimal. A method for solving the problem is based on its transformation to a constrained shortest path problem.     

Modelling transfer line design problem via a set partitioning problem

The design of a transfer line is considered. This line is used for a repetitive execution of a given set of operations to produce identical items. The line is composed of a sequence of workstations equipped with processing modules (blocks). Each block performs specific operations. The machined items move along the workstations in the same direction. There is the same cost associated with each workstation and different costs associated with diverse blocks. The problem is to determine the number of workstations, select a set of blocks and assign the selected blocks to the workstations so that, for each item, each operation is performed exactly once with total line cost to be minimized. The specificity of the problem is that all operations of the same workstation are performed in parallel. There are inclusion, exclusion, and precedence relations that restrict the assignment of blocks and operations to the same workstation and constrain the processing order of the operations on the transfer line. We suggest a reduction of this transfer line design problem to a simple set partitioning problem. This reduction is based on the concept of a locally feasible workstation.     

Balancing modular transfer lines with serial-parallel activation of spindle heads at stations

The paper deals with an as yet unexplored combinatorial optimization problem concerning balancing complex transfer lines in the machining/process environment. In contrast to similar problems for assembly lines, in transfer line balancing, tasks are grouped into blocks. All tasks of each block are executed simultaneously (in parallel) by one piece of equipment (spindle head). For the transfer lines considered in this paper, spindle heads at each station are activated in serial-parallel order. The set of all available spindle heads is known beforehand. Precedence, cycle time, compatibility, and parallelism constraints for the blocks and tasks are given. The line investment cost is estimated by the sum of block and station costs. The problem is to assign all tasks (using the available blocks) such that all constraints are respected and line investment cost is at a minimum. This paper focuses on solving the problem via a branch-and-bound algorithm. An approach for obtaining an efficient lower bound is offered, based on a reduction of the initial problem to a set partitioning problem. Computational experiments reveal that the proposed approach is efficient mathematically and can be used to solve practical transfer line design problems of a medium size.     

A heuristic multi-start decomposition approach for optimal design of serial machining lines

We study an optimal design problem for serial machining lines. Such lines consist of a sequence of stations. At every station, the operations to manufacture a product are grouped into blocks. The operations within each block are performed simultaneously by the same spindle head and the blocks of the same station are executed sequentially. The inclusion and exclusion constraints for combining operations into blocks and stations as well as the precedence constraints on the set of operations are given. The problem is to group the operations into blocks and stations minimizing the total line cost. A feasible solution must respect the given cycle time and all given constraints. In this paper, a heuristic multi-start decomposition approach is proposed. It utilizes a decomposition of the initial problem into several sub-problems on the basis of a heuristic solution. Then each obtained sub-problem is solved by an exact algorithm. This procedure is repeated many times, each time it starts with a new heuristic solution. Computational tests show that the proposed approach outperforms simple heuristic algorithms for large-scale problems.     

Scenario based robust line balancing: Computational complexity

This paper studies the following line balancing problem with uncertain operation execution times. Operations on the same product have to be assigned to the stations of a transfer line. The product moves along the stations in the same direction, and operations assigned to the same station are executed sequentially. Exclusion, inclusion and precedence relations are given on the set of operations. Operation execution times are uncertain in the sense that their set belongs to a given set of scenarios. The objective is to minimize the line cycle time, which is equal to the maximum total execution time of operations of the same station, for the worst scenario. An approach to reducing the scenario set is described. Several special cases of the problem are proved NP-hard and strongly NP-hard. Enumerative dynamic programming algorithms and problem-specific polynomial time algorithms are suggested for some cases.     

Exact solutions to a class of stochastic generalized assignment problems

This paper deals with a stochastic Generalized Assignment Problem with recourse. Only a random subset of the given set of jobs will require to be actually processed. An assignment of each job to an agent is decided a priori, and once the subset of jobs which have to be executed is known, reassignments can be performed if there are overloaded agents.We construct a convex approximation of the objective function that is sharp at all feasible solutions. We then present three versions of an exact algorithm to solve this problem, based on branch and bound techniques, optimality cuts, and a special purpose lower bound. Numerical results are reported.     

Yard crane scheduling in port container terminals

Yard cranes are the most popular container handling equipment for loading containers onto or unloading containers from trucks in container yards of land scarce port container terminals. However, such equipment is bulky, and very often generates bottlenecks in the container flow in a terminal because of their slow operations. Hence, it is essential to develop good yard crane work schedules to ensure a high terminal throughput. This paper studies the problem of scheduling a yard crane to perform a given set of loading/unloading jobs with different ready times. The objective is to minimize the sum of job waiting times. A branch and bound algorithm is proposed to solve the scheduling problem optimally. Efficient and effective algorithms are proposed to find lower bounds and upper bounds. The performance of the proposed branch and bound algorithm is evaluated by a set of test problems generated based on real life data. The results show that the algorithm can find the optimal sequence for most problems of realistic sizes.     

A branch and bound algorithm for hybrid flow shop scheduling problem with setup time and assembly operations

A hybrid flow shop scheduling problem (HFSP) with assembly operations is studied in this paper. In the considered problem, a number of products of the same kind are produced. Each product is assembled using a set of several parts. At first, the parts are produced in a hybrid flow shop and then they are assembled in an assembly stage to produce products. The considered objective is to minimize the completion time of all products (makespan). This problem has been proved strongly NP-hard, so in order to solve it, a hierarchical branch and bound algorithm is presented. Also, some lower and upper bounds are developed to increase the efficiency of the proposed algorithm. The numerical experiments are used to evaluate the performance of the proposed algorithm.     

A branch and bound algorithm for the acyclic subgraph problem

A branch and bound algorithm for the acyclic subgraph problem (feedback are set problem) is described. The branching scheme lexicographically enumerates all permutations, skipping initial segments known by some easy tests not to have any optimal completion. A lower bound for the number of feedback arcs is given by the size of any collection of disjoint cycles. We propose a heuristic algorithm to find a large collection. The size of the problems our branch and bound algorithm can solve varies from 25 to 34 nodes, depending on the nature of the problem.     

Optimal allocation and processing time decisions on non-identical parallel CNC machines: ϵ-constraint approach

When the processing times of jobs are controllable, selected processing times affect both the manufacturing cost and the scheduling performance. A well known example for such a case that this paper specifically deals with is the turning operation on a CNC machine. Manufacturing cost of a turning operation is a nonlinear convex function of its processing time. In this paper, we deal with making optimal machine-job assignments and processing time decisions so as to minimize total manufacturing cost while the makespan being upper bounded by a known value, denoted as ?-constraint approach for a bicriteria problem. We then give optimality properties for the resulting single criterion problem. We provide alternative methods to compute cost lower bounds for partial schedules, which are used in developing an exact (branch and bound) algorithm. For the cases where the exact algorithm is not efficient in terms of computation time, we present a recovering beam search algorithm equipped with an improvement search procedure. In order to find improving search directions, the improvement search algorithm uses the proposed cost bounding properties. Computational results show that our lower bounding methods in branch and bound algorithm achieve a significant reduction in the search tree size that we need to traverse. Also, our recovering beam search and improvement search heuristics achieve solutions within 1% of the optimum on the average while they spent much less computational effort than the exact algorithm.     

Optimisation of multi-position machines and transfer lines

A new optimisation problem for design of multi-position machines and automatic transfer lines is considered. To reduce the number of pieces of equipment, machining operations are grouped into blocks. The operations of the same block are performed simultaneously by one piece of equipment (multi-spindle head). At the studied design stage, constraints related to the design of blocks and workstations, as well as precedence constraints for operations are known. The problem consists in an optimal grouping of the operations into blocks minimizing the total number of blocks and workstations while reaching a given cycle time (productivity). A constrained shortest path algorithm is developed and tested.     

Block rearranging elements within matrix columns to minimize the variability of the row sums

Several problems in operations research, such as the assembly line crew scheduling problem and the k-partitioning problem can be cast as the problem of finding the intra-column rearrangement (permutation) of a matrix such that the row sums show minimum variability. A necessary condition for optimality of the rearranged matrix is that for every block containing one or more columns it must hold that its row sums are oppositely ordered to the row sums of the remaining columns. We propose the block rearrangement algorithm with variance equalization (BRAVE) as a suitable method to achieve this situation. It uses a carefully motivated heuristic—based on an idea of variance equalization—to find optimal blocks of columns and rearranges them. When applied to the number partitioning problem, we show that BRAVE outperforms the well-known greedy algorithm and the Karmarkar–Karp differencing algorithm.     

Flow-shop scheduling with setup and assembly operations

A scheduling model for a production system including machining, setup and assembly operations is considered. Production of a number of single-item products is ordered. Each product is made by assembling a set of several different parts. First, the parts are manufactured in a flow-shop consisting of multiple machines. Then, they are assembled into products on a single assembly stage. Setup operation and setup time are needed when a machine starts processing the parts or it changes items. The operations are partitioned into several blocks. Each block consists of the machining operations, the setup operations, and the assembly operation(s) for one or several products. The parts of the same item in a block are processed successively. The objective function is the mean completion time for all products. We consider a problem to partition the operations into blocks and sequence the parts in each block so as to minimize the objective function. Solution procedures using pseudo-dynamic programming and a branch-and-bound method are proposed. Computational experiments are carried out to evaluate the performance of the solution procedures. It has been found that a good near-optimal schedule is obtained efficiently by the proposed solution procedures.     

Approaches to Machine Load Balancing in Flexible Manufacturing Systems

The load balancing problem for a flexible manufacturing system concerns the allocation of operations to machines and of tools to magazines with limited capacity, while seeking to balance the workload on all machines. Previous attempts to tackle this problem have used integer programming and a specialized branch and bound procedure has been developed. A modified integer programming approach is proposed here. The problem has certain features which can be used advantageously for an approximate solution technique. The approximation technique is described and computational results presented. Extensions to the problem of pooling machines are also considered.     

An linear programming based lower bound for the simple assembly line balancing problem

The simple assembly line balancing problem is a classical integer programming problem in operations research. A set of tasks, each one being an indivisible amount of work requiring a number of time units, must be assigned to workstations without exceeding the cycle time. We present a new lower bound, namely the LP relaxation of an integer programming formulation based on Dantzig–Wolfe decomposition. We propose a column generation algorithm to solve the formulation. Therefore, we develop a branch-and-bound algorithm to exactly solve the pricing problem. We assess the quality of the lower bound by comparing it with other lower bounds and the best-known solution of the various instances from the literature. Computational results show that the lower bound is equal to the best-known objective function value for the majority of the instances. Moreover, the new LP based lower bound is able to prove optimality for an open problem.     

A branch-and-bound algorithm to minimize the line length of a two-sided assembly line

A new branch-and-bound algorithm is presented to solve the two-sided assembly line balancing problem of type 1 (TALB-1). First, a pair of two directly facing station is defined as a position, and then the two-sided assembly line (TAL) is relaxed to a one-sided assembly line (OAL). Some new lower bound on positions are computed, and dominance rules and reduction rules for the one-sided assembly line balancing problem of type 1 (OALB-1) are extended and incorporated into a station-oriented assignment procedure for the TALB-1 problem. Finally, the tests are carried out on a well-known benchmark set of problem instances, and experimental results demonstrate that the proposed procedure is efficient.     

具有工作站数量约束的多人工作站混合装配线平衡问题研究

针对装配线设计或改造过程中存在的因场地或成本原因导致的工作站数量不易变更的问题,研究了节拍已知情况下,具有工作站数量约束的多人工作站混合装配线平衡问题,建立以装配线总人数最小、工人负荷量标准差最小、各产品在各工作站装配时间与节拍之间的标准差最小为目标的数学模型,设计了一种结合差分进化的多目标混合遗传算法对该问题求解。通过案例计算以及与其他算法的对比分析表明,本文算法在收敛性和综合性能方面优于NSGAII和DEMO,在装配线人数和工人负荷标准差方面优于Roshani和Nezami提出的算法。     

A new AATP model with considering supply chain lead-times and resources and scheduling of the orders in flowshop production systems: A graph-theoretic view

The present study attempts to synchronize the scheduling problem with determining the advanced available-to-promise (AATP) in a flowshop system to enhance supplier profitability and service level. In the proposed model the AATP, scheduling and graph theory concept have been combined to find the optimum resource allocation and enable accurate estimations of machines scheduling, production costs and delivery dates. To find the near optimum solutions for the large size problems a genetic algorithm is developed, first the orders are ranked based on their scores which are estimated then the optimum cost is calculated by balancing profitability and constraints such as the availability of the machines or the available material in each workstation. Some computer simulated experiments are provided to evaluate the performance of the proposed algorithm.     

A branch and bound algorithm for determining locations of long-term care facilities

This paper focuses on the problem of determining locations for long-term care facilities with the objective of balancing the numbers of patients assigned to the facilities. We present a branch and bound algorithm by developing dominance properties, a lower bounding scheme and a heuristic algorithm for obtaining an upper bound for the problem. For evaluation of the suggested branch and bound algorithm, computational experiments are performed on a number of test problems. Results of the experiments show that the suggested algorithm gives optimal solutions of problems of practical sizes in a reasonable amount of computation time.     

Supply chain models for an assembly system with preprocessing of raw materials

In this paper, we investigate the material procurement and delivery policy in a production system where raw materials enter into the assembly line from two different flow channels. The system encompasses batch production process in which the finished product demand is approximately constant for an infinite planning horizon. Two distinct types of raw materials are passed through the assembly line before to convert them into the finished product. Of the two types of raw materials, one type requires preprocessing inside the facility before the assembly operation and other group is fed straightway in the assembly line. The conversion factors are assigned to raw materials to quantify the raw material batch size required. To analyze such a system, we formulate a nonlinear cost function to aggregate all the costs of the inventories, ordering, shipping and deliveries. An algorithm using the branch and bound concept is provided to find the best integer values of the optimal solutions. The result shows that the optimal procurement and delivery policy minimizes the expected total cost of the model. Using a test problem, the inventory requirements at each stage of production and their corresponding costs are calculated. From the analysis, it is shown that the rate and direction change of total cost is turned to positive when delivery rates per batch reaches close to the optimal value and the minimum cost is achieved at the optimal delivery rate. Also, it is shown that total incremental cost is monotonically increasing, if the finished product batch size is increased, and if, inventory cost rates are increased. We examine a set of numerical examples that reveal the insights into the procurement-delivery policy and the performance of such an assembly type inventory model.