There has been recent success in using polyhedral formulations of scheduling problems not only to obtain good lower bounds in practice but also to develop provably good approximation algorithms. Most of these formulations rely on binary decision variables that are a kind of assignment variables. We present quite simple polynomial{ time approximation algorithms that are based on linear programmi...

Among artificial intelligence approaches, artificial neural networks (ANNs) and genetic algorithm (GA) are widely applied for modification of materials property in engineering science in large scale modeling. In this work artificial neural network (ANN) and genetic algorithm (GA) were applied to find the optimal conditions for achieving the maximum hardness of Al6061 reinforced by multiwall car...

This paper considers a real-world industrial problem in order to minimize the (weighted) number of tardy jobs. This problem occurs in a company where due dates are associated with parts, and penalties incur when the parts are completed after the due dates, whatever the magnitude of the tardiness. Therefore, the objective function can be modelled as minimization of the (weighted) number of tardy...

In this paper proposes a fuzzy multi-objective hybrid Genetic and Bee colony optimization algorithm(GA-BCO) to find the optimal restoration of loads of power distribution network under fault.Restoration of distribution systems is a complex combinatorial optimization problem that should beefficiently restored in reasonable time. To improve the efficiency of restoration and facilitate theactivity...

This paper considers a real-world industrial problem in order to minimize the (weighted) number of tardy jobs. This problem occurs in a company where due dates are associated with parts, and penalties incur when the parts are completed after the due dates, whatever the magnitude of the tardiness. Therefore, the objective function can be modelled as minimization of the (weighted) number of tardy...

In this work we consider a multiobjective job shop problem with uncertain durations and crisp due dates. Ill-known durations are modelled as fuzzy numbers. We take a fuzzy goal programming approach to propose a generic multiobjective model based on lexicographical minimisation of expected values. To solve the resulting problem, we propose a genetic algorithm searching in the space of possibly a...

A kind of unrelated parallel machines scheduling problem is discussed. The memberships of fuzzy due dates denote the grades of satisfaction with respect to completion times with jobs. Objectives of scheduling are to maximize the minimum grade of satisfaction while makespan is minimized in the meantime. Two kind of genetic algorithms are employed to search optimal solution set of the problem. Bo...

In this paper, a multi-product single machine scheduling problem with the possibility of producing defected jobs, is considered. We concern rework in the scheduling environment and propose a mixed-integer programming (MIP) model for the problem.  Based on the philosophy of just-in-time production, minimization of the sum of earliness and tardiness costs is taken into account as the objective fu...

In this paper the problem of serial batch scheduling in a two-stage hybrid flow shop environment with minimizing Makesapn is studied. In serial batching it is assumed that jobs in a batch are processed serially, and their completion time is defined to be equal to the finishing time of the last job in the batch. The analysis and implementation of the prohibited transference of jobs among the mac...

In this paper we consider the single machine scheduling problem with integer release dates and the objective of minimising the sum of deviations of jobs’ completion times from a common integer due date. We present an efficient polynomial algorithm for the unit processing time case. We also show how to calculate in polynomial time the minimum non-restrictive due date for the general case.