The two-machine permutation flowshop scheduling problem to minimize makespan or total completion time criterion is addressed where setup times are considered to be separate from processing times. Setup times are relaxed to be random variables as opposed to the common assumption in the literature that setup times are exactly known (deterministic) in advance. The probability distributions of setu...

We characterize optimal policies for the problem of allocating a single server to a set of jobs from N families. Each job is an instance of demand for an item and is associated with a family, a holding cost rate, and a mean processing time. Setup times are required to switch from one family to another, but not within a family. We consider the case in which the order of jobs within the family is...

In this paper, the flow-shop scheduling problem with unrelated parallel machines at each stage as well as sequence-dependent setup times under minimization of the sum of earliness and tardiness are studied. The processing times, setup times and due-dates are known in advance. To solve the problem, we introduce a hybrid memetic algorithm as well as a particle swarm optimization algorithm combine...

• Introduction of a new batch scheduling formulation with parallel machines. Development two MIP-neighborhoods based on formulations. Matheuristics using ILS and GRASP frameworks. Real-life ship problem from the offshore oil gas industry. Improvement results literature in dataset actual data. In this paper, we address variant identical machines non-anticipatory family setup times to minimize to...

This paper considers the problem of scheduling a given number of jobs on a single machine to minimize total earliness and tardiness when family setup times exist. The paper proposes optimal branch-and-bound algorithms for both the group technology assumption and if the group technology assumption is removed. A heuristic algorithm is proposed to solve larger problems with the group technology as...

This paper introduces a new notion related to the traveling salesperson problem (TSP) — the notion of the TSP ratio. The TSP ratio of a TSP instance I is the sum of the marginal values of the nodes of I divided by the length of the optimal TSP tour on I, where the marginal value of a node i ∈ I is the difference between the length of the optimal tour on I and the length of the optimal tour on I...

Consider the problem in which n jobs that are classified into k types are to be scheduled on m identical machines without preemption. A machine requires a proper setup taking s time units before processing jobs of a given type. The objective is to minimize the makespan of the resulting schedule. We design and analyze an approximation algorithm that runs in time polynomial in n,m and k and compu...

In this paper, we study a Capacitated Lot Sizing Problem with Stochastic Setup Times (CLSP-SST).We describe a mathematical model that considers both regular costs (including production, setup and inventory holding costs) and expected overtime costs (related to the excess usage of capacity). The CLSP-SST is formulated as a two-stage stochastic programming problem. A procedure is proposed to effe...

The m-machine no-wait flowshop scheduling problem is addressed where setup times are treated as separate from processing times. The objective is to minimize total tardiness. Different dispatching rules have been investigated and three were found to be superior. Two heuristics, a simulated annealing (SA) and a genetic algorithm (GA), have been proposed by using the best performing dispatching ru...

Radiation therapy is one of the commonly used cancer therapies. The radiation treatment poses atuning problem: it needs to be effective enough to destroy the tumor, but it should maintain the func-tionality of the organs close to the tumor. Towards this goal the design of a radiation treatment has to becustomized for each patient. Part of this design are intensity matrices that defi...