Ali S. Kiran

Rescheduling on a single machine with part-type dependent setup times and deadlines

We consider the problem of rescheduling a facility modeled as a single machine in the face of newly arrived jobs with part-type dependent setup times. The facility contains a number of jobs that have been assigned due dates and scheduled so as to meet them. We wish to insert the new jobs into the existing schedule in a manner that will minimize the disruption of the jobs in the system and minimize the total weighted completion time or the maximum completion time of the new jobs. We provide a polynomial-time algorithm for the maximum completion time problem, prove that the total weighted completion time problem is NP-hard in the strong sense and study several of its special cases. In particular, we show that the case with reverse-agreeable weights (of which the unit weight problem is a special case) can be solved in polynomial time when the number of part types is fixed. We also present two heuristics for the problem with arbitrary weights and develop data-dependent worst-case error bounds. Extensive computational experiments show that the heuristics consistently obtain near-optimal solutions in very reasonable CPU times.

Simulation studies in job shop scheduling—II: Performance of priority rules

Abstract Major simulation studies of dynamic job shop scheduling problem and approaches taken to model dynamic job shops have been considered in Part I[25] of this paper. In Part II we focus our attention on basic results on relative effectiveness of priority rules in job shop simulation literature. Information on surveyed articles also is provided in the Appendix.

Single and multiple period layout models for automated manufacturing systems

Abstract Layout models for automated manufacturing systems are considered. The changes in product mix, part routings and process plans are incorporated into a stochastic single period layout model. A solution method, based on generating non-dominated layouts, is developed and illustrated. A dynamic programming formulation is also developed to capture the dynamic layout decisions in an automated manufacturing environment. A state space reduction approach is proposed for solving this multi-period model.

Simulation studies in job shop sheduling—I a survey

Abstract The dynamic job shop scheduling problem has been studied extensively during the last two decades. Because of the complexity of the dynamic job shop scheduling problem, numerous simulation studies have been conducted and published in the area. These studies fall into one of the following categories: the studies comparing and/or developing scheduling rules which will give good shop performance under a given set of job and shop parameters, and the studies investigating sensitivity of shop performance to job and shop parameters under a given set of scheduling rules. In the literature, shop performance has been evaluated in terms of (1) criteria based on job completion times, (2) criteria based on due dates, (3) criteria based on costs. This paper discusses approaches taken in major simulation studies of dynamic job shop scheduling problem according to the above classification.

Optimal pickup point location on material handling networks

The optimal location of a pickup point on a material handling network is considered. The pickup point is defined as the material exchange point between the material handling system (MHS) and a station. The problem is defined as that of choosing the location of the pickup point to minimize the total cost of material movement in the MHS. A facility location model on directed networks has been developed, and strongly polynomial solution methods are presented.

A location problem on unicyclic networks: Balanced case

Abstract The problem of locating n stations on a unicyclic unidirectional network is considered. We formulated the problem as an integer program for the case of a balanced flow matrix, i.e., the total inflow to a station equals the total outflow from that station. The integer programming formulation reduces the problem to a station sequencing problem regardless of the actual station locations on the network. Furthermore, the empirical evidence suggests that the LP solutions to the relaxed IP formulations are optimal.

An integrated simulation approach to design of flexible manufacturing systems

Simulation has been used in the design of manufacturing cells at General Dynamics-Pomona Division. At the preliminary design stage, mean value analysis has been used to define basic system characteristics and to develop design alternatives. Siman simula tion language and a specifically designed user interface have been utilized in evaluating alternative designs. The performance of the final designs has been analyzed using statistical techniques.

Tardiness Heuristic For Scheduling Flexible Manufacturing Systems

Abstract This paper evaluates the tardiness performance of a sampling-based adaptive heuristic in a dynamic manufacturing environment. A test bed, following a real world manufacturing system, has been developed. The proposed algorithm has been implemented in this simulated environment. After fine tuning the algorithm, it has been tested in various shop conditions. The results of these simulation studies are summarized.

Synergy of artificial neural networks and knowledge-based expert systems for intelligent FMS scheduling

A hybrid architecture that integrates artificial neural networks and knowledge-based expert systems to generate solutions for the real-time scheduling of flexible manufacturing systems is described. The artificial neural networks perform pattern recognition and, due to their inherent characteristics, support the implementation of automated knowledge acquisition and refinement schemes through a feedback mechanism. The artificial neural network structures enable the system to recognize patterns in the tasks to be solved in order to select the best scheduling rule according to different demands. The knowledge-based expert systems are the higher-order elements which drive the inference strategy and interpret the constraints and restrictions imposed by the upper levels of the flexible manufacturing system control hierarchy. The level of self-organization achieved provides a system with a higher probability of success than traditional approaches

Optimum central storage location in flexible manufacturing cells

Abstract Optimum storage location for work-in-progress in flexible manufacturing cells is considered. A measure for traffic intensity between stations and central storage area is defined. The problem is investigated under discrete and continuous space assumptions and known layout models have been adapted to the new context. In the discrete case, the problem is transformed to a generalized assignment model which can be solved efficiently. Applicability of continuous layout models under different distance measures is discussed for the continuous case. Various examples are supplied to illustrate the approaches.