Nowadays project management is a key component in introductory operations management. The educators and the researchers in these areas advocate representing a project as a network and applying the solution approaches for network models to them to assist project managers to monitor their completion. In this paper, we evaluated project’s completion time utilizing the Q-learning algorithm. So the ...

RACT : We consider the two-machine flowshop scheduling problem where jobs have random processing times are bounded within certain intervals. The objective is to minimize total completion time of all jobs. The decision of a solution for the problem has to be made based on the lower and upper bounds on job processing times since this only information available. The problem is NP-hard since the sp...

This paper explores the flexile flow lines where setup times are sequence- dependent. The optimization criterion is the minimization of total weighted completion time. We propose an iterated greedy algorithm (IGA) to tackle the problem. An experimental evaluation is conducted to evaluate the proposed algorithm and, then, the obtained results of IGA are compared against those of some other exist...

In this paper we study the scheduling problem in which each customer order consists of several jobs of different types, which are to be processed on m facilities. Each facility is dedicated to the processing of only one type of jobs. All jobs of an order have to be delivered to the customer at the same time. The objective is to schedule all the orders to minimize the total weighted order comple...

We study the special case of the m machine ow shop problem in which the processing time of each operation of job j is equal to p j ; this variant of the ow shop problem is known as the proportionate ow shop problem. We show that for any number of machines and for any regular performance criterion we can restrict our search for an optimal schedule to permutation schedules. Moreover, we show that...

In this paper we study an extension of the single machine scheduling problem with the total weighted completion time objective, where there is a single non-renewable resource consumed by the jobs, having an initial stock and some additional replenishments over time. We prove that this problem is NP-hard in the strong sense, and provide an FPTAS for a special case with two supply dates.

We consider a single machine scheduling problem to minimize the weighted completion time variance. This problem is known to be NP-hard in the strong sense. We propose a lower bound based on splitting of jobs and the Viswanathkumar and Srinivasan procedure and a heuristic. The test on more than 2000 instances shows that this lower bound is very tight.