This paper focuses on a stochastic scheduling problem in which n immediately available jobs are to be scheduled jointly with the preventive maintenance in a single machine subject to breakdowns. The objective is to minimize expected total earliness and tardiness costs with a common due-date. The problem of scheduling only n jobs to minimize total earliness and tardiness costs in a single machin...

We investigate an online version of a basic scheduling problem where a set of jobs has to be scheduled on a number of identical machines so as to minimize the makespan. The job processing times are known in advance and preemption of jobs is allowed. Machines are non-continuously available, i.e., they can break down and recover at arbitrary time instances not known in advance. New machines may b...

Dynamic job shop scheduling (DJSS) problems are combinatorial optimisation problems that have been extensively studied in the literature due to their difficulty and their applicability to real-world manufacturing systems, e.g., car manufacturing systems. In a DJSS problem instance, jobs arrive on the shop floor to be processed on specific sequences of machines on the shop floor and unforeseen e...

In this paper, we study N-policy for a finite population Bernoulli feedback queueing model for machine repair problem with degraded failure. The running times of the machines between breakdowns have an exponential distribution. The repair times of the machines are independent and identically distributed random variables. If at any time a machine fails, it is sent to the repairman for repairing,...

This paper considers a scheduling problem with uncertain processing times and machine breakdowns in industriall/office workplaces and solves it via a novel robust optimization method. In the traditional robust optimization, the solution robustness is maintained only for a specific set of scenarios, which may worsen the situation  for new scenarios. Thus, a two-stage predictive algorithm is prop...

In this paper, we consider a multi-period, multi-product production planning problem where the production rate and the customer service level are random variables due to machine breakdowns. In order to determine robust production plans, constraints are introduced in the stochastic capacitated lot-sizing problem to ensure that a prespecified customer service level is met with high probability. T...