Edward Ignall

Bio: Edward Ignall is an academic researcher from Columbia University. The author has contributed to research in topics: Software deployment & Inventory control. The author has an hindex of 17, co-authored 36 publications receiving 1549 citations. Previous affiliations of Edward Ignall include Cornell University.

Application of the Branch and Bound Technique to Some Flow-Shop Scheduling Problems

Abstract: The branch-and-bound technique of Little, et al. and Land and Doig is presented and then applied to two flow-shop scheduling problems. Computational results for up to 9 jobs are given for the 2-machine problem when the objective is minimizing the mean completion time. This problem was previously untreated. Results for up to 10 jobs, including comparisons with other techniques, are given for the 3-machine problem when the objective is minimizing the makespan.

Response Areas for Two Emergency Units

Abstract: This paper gives a model in which two urban emergency service units such as fire engines or ambulances cooperate in responding to alarms or calls from the public in a specified region of a city. Given the home locations of the units and the spatial distribution of alarm rates, it is possible to specify which unit should respond to each alarm by defining a response area for each unit. The average response time to alarms and the workload of each unit are calculated as functions of the boundary that separates their response areas. The boundaries that minimize average response time and the ones that equalize workload are determined. Some boundaries can be dominated, in the sense that another boundary improves both workload balance and response time. The set of undominated boundaries is found.

Optimality of Myopic Inventory Policies for Several Substitute Products

Abstract: Multiproduct inventory systems with proportional ordering costs and stochastic demands are studied. New conditions are obtained under which a myopic ordering policy (a policy of minimizing expected cost in the current period alone) is optimal for a sequence of periods for all initial inventory levels. An important one of these, the substitute property, holds when the myopic policy is such that increasing the initial inventory of one product does not increase the quantity ordered of any product. Conditions on the one period expected holding and shortage cost function, which are of independent interest in nonlinear programming, are shown to imply the substitute property. Applications of these conditions to models with storage or investment limitations and to a multiechelon model are given. Under backlogging the usual extension to a fixed delivery lag is obtained. Some non-stationary cases are also treated.

Optimal Continuous Review Policies for Two Product Inventory Systems with Joint Setup Costs

Abstract: Minimum average cost ordering policies for continuously reviewed two product inventory systems with joint setup costs are sought. Disappointly, the optimal policy, even in a simple symmetric case, is not always simple: For some values of cost and demand parameters, a policy that would be difficult to implement is optimal. Markov Renewal Programming is used to find the region in parameter space where a given policy is optimal.

The Output of A Two-Stage System with Unreliable Machines and Limited Storage

Abstract: Buffer storage allows the decoupling of successive stages of large automatic production systems, which can be important when the machines sometimes fail. System designers should know how much added buffer capacity increases the hourly output of such systems. Previously available methods for predicting this increase treat systems with one machine in each stage. We present a computationally simple heuristic procedure for estimating hourly line output for two stage systems in which each stage may have several machines.

Optimization and Approximation in Deterministic Sequencing and Scheduling: a Survey

Abstract: The theory of deterministic sequencing and scheduling has expanded rapidly during the past years. In this paper we survey the state of the art with respect to optimization and approximation algorithms and interpret these in terms of computational complexity theory. Special cases considered are single machine scheduling, identical, uniform and unrelated parallel machine scheduling, and open shop, flow shop and job shop scheduling. We indicate some problems for future research and include a selective bibliography.

A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem

Abstract: In a general flow-shop situation, where all the jobs must pass through all the machines in the same order, certain heuristic algorithms propose that the jobs with higher total process time should be given higher priority than the jobs with less total process time. Based on this premise, a simple algorithm is presented in this paper, which produces very good sequences in comparison with existing heuristics. The results of the proposed algorithm have been compared with the results from 15 other algorithms in an independent study by Park [13], who shows that the proposed algorithm performs especially well on large flow-shop problems in both the static and dynamic sequencing environments.

Branch-and-Bound Methods: A Survey

Abstract: The essential features of the branch-and-bound approach to constrained optimization are described, and several specific applications are reviewed. These include integer linear programming Land-Doig and Balas methods, nonlinear programming minimization of nonconvex objective functions, the traveling-salesman problem Eastman and Little, et al. methods, and the quadratic assignment problem Gilmore and Lawler methods. Computational considerations, including trade-offs between length of computation and storage requirements, are discussed and a comparison with dynamic programming is made. Various applications outside the domain of mathematical programming are also mentioned.

Perishable Inventory Theory: A Review

Abstract: This paper reviews the relevant literature on the problem of determining suitable ordering policies for both fixed life perishable inventory, and inventory subject to continuous exponential decay. We consider both deterministic and stochastic demand for single and multiple products. Both optimal and sub-optimal order policies are discussed. In addition, a brief review of the application of these models to blood bank management is included. The review concludes with a discussion of some of the interesting open research questions in the area.