Chelliah Sriskandarajah

A Survey of Machine Scheduling Problems with Blocking and No-Wait in Process

An important class of machine scheduling problems is characterized by a no-wait or blocking production environment, where there is no intermediate buffer between machines. In a no-wait environment, a job must be processed from start to completion, without any interruption either on or between machines. Blocking occurs when a job, having completed processing on a machine, remains on the machine until a downstream machine becomes available for processing. A no-wait or blocking production environment typically arises from characteristics of the processing technology itself, or from the absence of storage capacity between operations of a job. In this review paper, we describe several well-documented applications of no-wait and blocking scheduling models and illustrate some ways in which the increasing use of modern manufacturing methods gives rise to other applications. We review the computational complexity of a wide variety of no-wait and blocking scheduling problems and describe several problems which remain open as to complexity. We study several deterministic flowshop, jobshop, and openshop problems and describe efficient and enumerative algorithms, as well as heuristics and results about their performance. The literature on stochastic no-wait and blocking scheduling problems is also reviewed. Finally, we provide some suggestions for future research directions.

Sequencing of parts and robot moves in a robotic cell

In this paper, we deal with the problem of sequencing parts and robot moves in a robotic cell where the robot is used to feed machines in the cell. The robotic cell, which produces a set of parts of the same or different types, is a flow-line manufacturing system. Our objective is to maximize the long-run average throughput of the system subject to the constraint that the parts are to be produced in proportion of their demand. The cycle time formulas are developed and analyzed for this purpose for cells producing a single part type using two or three machines. A state space approach is used to address the problem. Both necessary and sufficient conditions are obtained for various cycles to be optimal. Finally, in the case of many part types, the problem of scheduling parts for a specific sequence of robot moves in a two machine cell is formulated as a solvable case of the traveling salesman problem.

Sequencing and Scheduling in Robotic Cells: Recent Developments

A great deal of work has been done to analyze the problem of robot move sequencing and part scheduling in robotic flowshop cells. We examine the recent developments in this literature. A robotic flowshop cell consists of a number of processing stages served by one or more robots. Each stage has one or more machines that perform that stage’s processing. Types of robotic cells are differentiated from one another by certain characteristics, including robot type, robot travel-time, number of robots, types of parts processed, and use of parallel machines within stages. We focus on cyclic production of parts. A cycle is specified by a repeatable sequence of robot moves designed to transfer a set of parts between the machines for their processing.We start by providing a classification scheme for robotic cell scheduling problems that is based on three characteristics: machine environment, processing restrictions, and objective function, and discuss the influence of these characteristics on the methods of analysis employed. In addition to reporting recent results on classical robotic cell scheduling problems, we include results on robotic cells with advanced features such as dual gripper robots, parallel machines, and multiple robots. Next, we examine implementation issues that have been addressed in the practice-oriented literature and detail the optimal policies to use under various combinations of conditions. We conclude by describing some important open problems in the field.

Design and operational issues in AGV-served manufacturing systems

Automated Guided Vehicle (AGV) systems are already in widespread use and their importance for material handling is expected to grow rapidly. The advantages that such systems can offer include increased flexibility, better space utilization, improved factory floor safety, reduction in overall operating cost, and easier interface with other automated systems. This survey paper focuses on design and operational issues that arise in AGV systems. The objectives of the paper are to unify various lines of research related to AGVs and to suggest directions for future study. We consider problems arising in flowpath design, fleet sizing, job and vehicle scheduling, dispatching and conflict-free routing. Flowpath design problems address computationally intractable issues in the physical layout of a single loop and complex networks. Transportation and related models, waiting line analysis and simulation approaches are used to address fleet sizing questions. Scheduling issues focus on three flowpath layouts. In line layouts, the most important issues include finding an efficient job sequencing algorithm and identifying optimal AGV launch times. In loop layouts, issues such as joint scheduling of the job and AGV schedules, interface with a larger manufacturing system, dynamic job arrivals, and the location of the AGV parking area, are important. For complex network layouts, joint scheduling, heuristic dispatching rules, and conflict-free routing of AGVs, are considered. We identify the inefficiencies that result from addressing these issues in isolation, suggesting the need for integration. We also provide a summary of the most important open research issues related to all the above topics.

Scheduling in Robotic Cells: Classification, Two and Three Machine Cells

This paper considers the scheduling of operations in a manufacturing cell that repetitively produces a family of similar parts on two or three machines served by a robot. We provide a classification scheme for scheduling problems in robotic cells. We discuss finding the robot move cycle and the part sequence that jointly minimize the production cycle time, or equivalently maximize the throughput rate. For multiple part-type problems in a two-machine cell, we provide an efficient algorithm that simultaneously optimizes the robot move and part sequencing problems. This algorithm is tested computationally. For a three-machine cell with general data and identical parts, we address an important conjecture about the optimality of repeating one-unit cycles, and show that such a procedure dominates more complicated cycles producing two units. For a three-machine cell producing multiple part-types, we prove that four out of the six potentially optimal robot move cycles for producing one unit allow efficient identification of the optimal part sequence. Several efficiently solvable special cases with practical relevance are identified, since the general problem of minimizing cycle time is intractable. Finally, we discuss ways in which a robotic cell converges to a steady state.

Parallel machine scheduling with a common server

This paper considers the nonpreemptive scheduling of a given set of jobs on several identical, parallel machines. Each job must be processed on one of the machines. Prior to processing, a job must be loaded (setup) by a single server onto the relevant machine. The paper considers a number of classical scheduling objectives in this environment, under a variety of assumptions about setup and processing times. For each problem considered, the intention is to provide either a polynomial- or pseudo-polynomial-time algorithm, or a proof of binary or unary NP-completeness. The results provide a mapping of the computational complexity of these problems.

The Integrated Production and Transportation Scheduling Problem for a Product with a Short Lifespan

The integrated production and transportation scheduling problem (PTSP) with capacity constraints is common in many industries. An optimal solution to PTSP requires one to simultaneously solve the production scheduling and the transportation routing problems, which requires excessive computational time, even for relatively small problems. In this study, we consider a variation of PTSP that involves a short shelf life product; hence, there is no inventory of the product in process. Once a lot of the product is produced, it must be transported with nonnegligible transportation time directly to various customer sites within its limited lifespan. The objective is to determine the minimum time required to complete producing and delivering the product to meet the demand of a given set of customers over a wide geographic region. This problem is NP-hard in the strong sense. We analyze the properties of this problem, develop lower bounds on the optimal solution, and propose a two-phase heuristic based on the analysis. The first phase uses either a genetic or a memetic algorithm to select a locally optimal permutation of the given set of customers; the second phase partitions the customer sequence and then uses the Gilmore-Gomory algorithm to order the subsequences of customers to form the integrated schedule. Empirical observations on the performance of this heuristic are reported.

Scheduling in robotic cells: Complexity and steady state analysis

Abstract This paper considers the scheduling of operations in a manufacturing cell that repetitively produces a family of similar parts on several machines served by a robot. The decisions to be made include finding the robot move cycle and the part sequence that jointly minimize the production cycle time, or equivalently maximize the throughput rate. We focus on complexity issues and steady state performance. In a three machine cell producing multiple part-types, we prove that in two out of the six potentially optimal robot move cycles for producing one unit, the recognition version of the part sequencing problem is unary NP -complete. The other four cycles have earlier been shown to define efficiently solvable part sequencing problems. The general part sequencing problem not restricted to any robot move cycle in a three machine cell is shown to be unary NP -complete. Finally, we discuss the ways in which a robotic cell converges to a steady state.

Lot streaming and scheduling heuristics for m -machine no-wait flowshops

Abstract The objective of this paper is to minimize makespan in m -machine no-wait flowshops with multiple products requiring lot streaming. A ‘product’ here implies many identical items. ‘Lot streaming’ creates sublots to move the completed portion of a production lot to downstream machines so that machine operations can be overlapped. For the single product case with fixed number of sublots we obtain optimal continuous-sized sublots and then use a heuristic to find integer-sized sublots. For the multi-product continuous-sized sublots case we show that the optimal sequencing of products may be attained by solving a traveling salesman problem. We then construct another heuristic to yield integer-sized sublots. Finally, we evaluate the use of genetic algorithmic meta-heuristics for the interacting decision phases in simultaneous lot streaming and sequencing. We conclude that while GA may deliver makespans comparable in quality to those given by heuristic methods that cleverly exploit problem features particular to lot streaming, GA loses out in computational efficiency. On the other hand, GA can optimize the number of sublots for each product — a task for which neither an analytical nor a heuristic method presently exists.

Tabu search-based heuristics for cellular manufacturing systems in the presence of alternative process plans

Abstract When alternative process plans are considered in cellular manufacturing systems, there is potential for performing an operation required of a part on alternative machines. Under these circumstances, the cell formation problem of determining the assignment of parts and machines to each manufacturing cell can be viewed as being divided into two phases. The first phase deals with the problem of determining the number of machines of each type and a unique process plan for each part. In the second phase, the assignment of parts and machines to each manufacturing cell should be determined. This research examines the first-phase problem. A realistic formulation of the model is presented when the product-part mixes are stable over the planning horizon. As the problem is proven NP-hard in the strong sense, two different higher-level heuristics, based upon a concept known as tabu search, are presented. Each heuristic is further extended into two methods: 1 and 2. An extensive statistical analysis, based up...