Cemalettin Öztürk

Simultaneous Balancing and Scheduling of Flexible Mixed Model Assembly Lines with Sequence-Dependent Setup Times

We consider Simultaneous Balancing and Scheduling of Flexible Mixed Model Assembly Lines with Sequence-Dependent Setup Times (SBSFMMAL-SDST). We propose alternate Mixed Integer Programming (MIP) and Constraint Programming (CP) formulations. Our experiments show that while the MIP models could not solve relatively small instances, the CP approach seems more promising.

Balancing and scheduling of flexible mixed model assembly lines

Mixed model assembly line literature involves two problems: balancing and model sequencing. The general tendency in current studies is to deal with these problems in different time frames. However, in today’s competitive market, the mixed model assembly line balancing problem has been turned into an operational problem. In this paper, we propose mixed integer programming (MIP) and constraint programming (CP) models which consider both balancing and model sequencing within the same formulation along with the optimal schedule of tasks at a station. Furthermore, we also compare the proposed exact models with decomposition schemes developed for solving different instances of varying sizes. This is the first paper in the literature which takes into account the network type precedence diagrams and limited buffer capacities between stations. Besides, it is the first study that CP method is applied to balancing and scheduling of mixed model assembly lines. Our empirical study shows that the CP approach outperforms the MIP approach as well as the decomposition schemes.

A note on “A mixed integer programming model for advanced planning and scheduling (APS)”

In a recent paper, Chen and Ji [Chen, K., Ji, P., 2007. A mixed integer programming model for advanced planning and scheduling (APS). European Journal of Operational Research 181, 515-522] develop a mixed integer programming model for advanced planning and scheduling problem that considers capacity constraints and precedence relations between the operations. The orders require processing of several operations on eligible machines. The model presented in the above paper works for the case where each operation can be processed on only one machine. However, machine eligibility means that only a subset of machines are capable of processing a job and this subset may include more than one machine. We provide a general model for advanced planning and scheduling problems with machine eligibility. Our model can be used for problems where there are alternative machines that an operation can be assigned to.

A Constraint Programming Model for Balancing and Scheduling of Flexible Mixed Model Assembly Lines with Parallel Stations

Abstract In this paper, we study flexible mixed model assembly lines with serially connected stages where stages may have one or more parallel stations. Station parallelism in flexible mixed model assembly lines improves system reliability and enables rapid adaptability to customer demand fluctuations. In this paper we consider task assignment, model and task scheduling problems simultaneously. Due to its success in solving combinatorial problems, we develop a Constraint Programming model for the problem and test its performance using various size instances. The results reveal that, the model outperforms a Mixed Integer Programming model and a decomposition scheme given in the literature.

Optimisation and heuristic approaches for assigning inbound containers to outbound carriers

ABSTRACT Due to economical and/or geographical constraints, most of the time overseas containers cannot be directly shipped to their destinations. These containers visit transhipment ports where they are first unloaded and temporarily stored and then loaded onto smaller vessels (feeders) to be transported to their final destinations. The assignment of these containers to outbound vessels necessitates several factors to be taken into account simultaneously. In this paper, we develop a mathematical model to reflect multiple objectives with priorities and to assign these containers to different vessels at the transit container port terminal. Although we solve a single-objective (with the weighted sum of objectives) mathematical model to optimality, we also propose two heuristic approaches to solve this complex problem for a transit agency. The first heuristic is shipment based and has four variants differing in how the opportunity costs of the assignments are calculated. The second greedy heuristic is trip based, where the goal is to maximise the capacity utilisation of the vessels. The heuristics return very promising solutions in ignorable computational times. We also provide real-life cases and present our conclusions.

Cyclic Scheduling of Flexible Mixed Model Assembly Lines

Abstract Mixed model assembly lines are used to produce multiple copies of given minimum part set (MPS). Considering only one copy (cycle) of the MPS while solving the mixed-model balancing and scheduling problem yields suboptimal solutions since blocking and idle times of stations between repeated copies are ignored. Modeling and solving this problem in a cyclic manner can significantly overcome these inefficiencies and improve the throughput of the line. In this paper, after investigating the nature of the problem, we propose exact and heuristic methods for practical applications and evaluate their performances on various size test instances.