We investigate the stochastic flow shop problem with m machines and general distributions for processing times. No analytic method exists for solving this problem, so we looked instead at heuristic methods. We devised three constructive procedures with modest computational requirements, each...

We address the single-machine stochastic scheduling problem with an objective of minimizing total expected earliness and tardiness costs, assuming that processing times follow normal distributions and due dates are decisions. We develop a branch and bound algorithm to find optimal solutions to...

The deterministic multi-product single-machine production and inventory problem is one of the simplest models in which production and inventory factors interact. There is at present no algorithm available which solves the problem optimally, and several different types of approaches have been...

We investigate how to allocate work in stochastic assembly systems so as to maximize throughput. We use Markov models for systems with exponential processing times and simulation-based methods for other probability distributions. We find that assembly systems should be unbalanced in the...

A simple algorithm is developed for the problem of assigning days off to full-time staff given a cyclic seven-day demand pattern. The formulation assumes that employees are entitled to two consecutive days off each week and that the objective is to find a minimum staff size capable of meeting...

Recent research studies of job shop scheduling have begun to examine the interaction between sequencing priorities and the method of assigning due-dates. This paper surveys the tactical aspects of this interaction, focusing primarily on average tardiness as a measure of scheduling effectiveness....

We consider the situation of a single item having a deterministic, time-varying demand pattern. Production lot sizes, so as to minimize the total of setup and carrying costs, are to be determined subject to production capacity restrictions that can vary with time. Two important theorems...