Mohamed I. Dessouky

Flowshop scheduling with identical jobs and uniform parallel machines

The single-stage scheduling problem to minimize the makespan of identical jobs on uniform parallel machines is known to be solvable in polynomial-time. We extend this work to consider multi-stage systems with flowshop configuration. We show that the 2-stage problem may also be solved in polynomial-time and for the number of stages greater than two, the problem is shown to be NP-hard. We present a branch and bound procedure which provides an optimal solution to the 3-stage problem, and a fast heuristic procedure that is shown to provide good approximate solutions on sample problems. This heuristic is a natural extension of the 2-stage polynomial-time procedure. We develop theoretical bounds showing that the maximum deviation between the solution derived by the heuristic procedure and the optimal solution is bounded by the maximum processing time of a machine at the second stage, independent of the number of jobs and the processing times at the first and third stages. We also show that the heuristic provides an approximate solution bounded by a ratio of 1.75 to the optimal solution.

Scheduling collection of recyclable material at Northern Illinois University campus using a two-phase algorithm

This paper considers the problem of collecting recyclable materials in a large university campus with many buildings. It models the problem as a vehicle routing problem with additional constraints and applies a two-phase algorithm in order to provide a heuristic solution.

Scheduling identical jobs on uniform parallel machines with random processing times

Abstract For the problem of scheduling identical jobs on a set of uniform parallel machines with random processing times, methods are given for optimizing the expected sum of weighted completion times and the probability of meeting a common due date.

Optimal selection of sampling locations and c-chart parameters

Abstract This paper presents a method for designing a statistical process contral program over the attributes of a multi-stage discrete part manufacturing system. The objective of the program is to minimize the sum of the costs of bad quality, inspection, searching for special causes of variation, process adjustment, and reworking of rejected items. The costs are affected by two interacting levels of decision, macro and micro. The macro level selects the points in the process at which quality control is exercised, referred to here as quality control windows. The micro level determines the control chart parameters, namely frequency of sampling, the sample size, and the chart range.