Ramchandran Jaikumar

A generalized assignment heuristic for vehicle routing

Abstract : We consider a common variant of the vehicle routing problem in which a vehicle fleet delivers products stored at a central depot to satisfy customer orders. Each vehicle has a fixed capacity, and each order uses a fixed portion of vehicle capacity. The routing decision involves determining which of the demands will be satisfied by each vehicle and what route each vehicle will follow in servicing its assigned demand in order to minimize total delivery cost. We present a heuristic for this problem in which an assignment of customers to vehicles is obtained by solving a generalized assignment problem with an objective function that approximates delivery cost. This heuristic has many attractive features. It has outperformed the best existing heuristics on a sample of standard test problems. It will always find a feasible solution if one exists, something no other existing heuristic can guarantee. It can be easily adapted to accommodate many additional problem complexities. By parametrically varying the number of vehicles in the fleet, our method can be used to optimally solve the problem of finding the minimum size fleet that can feasibly service the specified demand.

Requirements for successful implementation of new manufacturing technologies

Abstract This paper addresses the issue of why many U.S. companies have had major problems implementing “programmable automation” technologies in a manner to exploit their full potential. Many competitors in Japan and Europe have been much more successful. The theme of the paper is that the real impediment to the effective use of this new manufacturing hardware lies in some deeply entrenched attitudes and ways of doing things that are incompatible with the requirements and unique capabilities of the new hardware. Barriers to successful implementation are explored and implications for managerial practice are discussed.

Dynamic Operational Policies in an Automated Warehouse

Abstract In this paper we consider the optimal relocation of pallets with a high expectancy of retrieval within each storage rack of an automated warehouse to meet the fluctuating, short-term throughput requirements imposed on the automated storage-retrieval machines. The prepositioning of these pallets closer to the input/output point of each rack during off-peak periods will reduce the expected travel time for the storage/retrieval machines during future peak periods of the planning horizon. As the model has been abstracted from an actual operating environment, we first describe the environment in which the problem has been posed. We then exploit the special structure of the problem to develop conditions that an optimal relocation policy should satisfy. Based on these optimality conditions, we develop a very efficient optimal relocation algorithm. Finally, we present the performance of several relocation policies in the warehouse studied. Handled by the Department of Manufacturing and Automated Production.

Robust Process Control at Cerestar'S Refineries

With annual sales of over

Japanese flexible manufacturing systems: Impact on the United States

2 billion, Cerestar is Europes lead-ing manufacturer of made-to-order wheat- and corn-based starch products. Cerestar relies on refineries that are highly automated and require large fixed investments. Starting in 1993, we developed Robust Process Control (RPC) to increase average throughput and reduce throughput variation by combining engineering principles with OR/MS techniques. RPC includes a mathematical-programming model to reduce downtimes due to product switchovers, models for process optimization, and dynamic control models for process-flow synchronization. Cerestar implemented the resulting decision support system at eight refineries in six countries. It has increased average daily throughputs by 20 percent and reduced average throughput variation by 50 percent. Concomitantly, the refineries have reduced their consumption of supplies and utilities. In addition to over

Dynamic scheduling of automated guided vehicles for a certain class of systems

11 million in annual benefits, RPC has had major strategic and organizational impact.

The Tug Fleet Size Problem for Barge Line Operations: A Polynomial Algorithm

Abstract A new technology, computer integrated manufacturing, has the potential to radically transform metal forming and metal cutting industries. In this paper, the evolution of this technology in the machine tool industry is studies in both the United States and Japan. We find that the boundaries of the machine tool industry have expanded to include a wide variety of firms in different industries. The competitive implications of the technological trends and changes in the industrial structure of the machine tool industry are discussed. Finally, we offer some policy guidelines to meet the new challenge.

An Algorithm for the Space-Shuttle Scheduling Problem

Abstract Many contemporary manufacturing facilities employ automated guided vehicles (AGVs) for material handling. These vehicles are independently addressable and centrally controlled. In this paper we develop analytical results about the design and operation of certain types of AGV systems and some associated production planning and scheduling problems. Specifically, we analyze the assignment of part types to machines, the sequencing of jobs on each machine, the determination of the AGV fleet size, and the scheduling/dispatching of the AGVs. Given the high capital cost involved in automation, our primary objective is to maximize machine utilization. For a given level of service, we will minimize the AGV travel time. It is shown that by exploiting the special structure exhibited by many systems found in practice, polynomial time algorithms can provide full machine utilization under realistic conditions.

Incorporating operator–process interactions in process control: A framework and an application to glucose refining

In this paper the problem of minimizing the number of tugs required to transport a given number of barges between different ports in a river system is considered. The problem has traditionally been viewed as a vehicle routing problem and thus routing heuristics have been used. Advantage is taken of the feature that transfer time at ports is negligible, and the problem is modeled differently. A one-pass algorithm is developed which solves the problem in O ( n ) time. Extensions are made dealing with general river system structures and stochasticity in the demand pattern.

Price discounting in multi-echelon distribution systems

The mission scheduling problem of the NASA space-shuttle program requires a selection of mission launch times that minimize the number of missions flown late and that satisfy early start time and resource constraints. We present an algorithm for this problem that is easy to program, requires little computation and, under certain restrictive assumptions, provides an optimal solution. Computational experience with a test case is discussed.