this study is focused on developing an integrated optimization-simulation based genetic algorithm model (iosga) to develop the operational policies for a multi-purpose reservoir system. the objective function of the optimization model is considered to be a linear function of reliability (rel), resiliency (res), and vulnerability (vul) of the river-reservoir system. genetic algorithm (ga) is emp...

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 a genetic algorithm (GA) with dualfitness function is proposed and applied to solve the deterministic identical machine scheduling problem. The mating fitness function value was used to determine the mating for chromosomes, while the selection fitness function value was used to determine their survivals. The performance of this algorithm was tested on deterministic identical machi...

This paper considers a two-stage assembly flow shop scheduling problem. When all parts of each product are completed in the first stage, they are assembled into a final product on an assembly machine in the second stage. In order to reduce the delivery cost, completed products can be held until completion of some other products to be delivered in a same batch. The proposed problem addresses sch...

In the present work, SDST flow shop scheduling with minimizing the weighted sum of total weighted tardiness and makespan have been considered simultaneously. Four modified heuristic have been proposed for preliminary viable sequence. Sequence obtained from the modified heuristics is combined with the initial seed sequence of genetic algorithm and called as Genetic Algorithm (GA). Hence four dif...

abstract: this paper considers the problem of scheduling n jobs on m unrelated parallel machines with sequence-dependent setup times. to better comply with industrial situations, jobs have varying due dates and ready times and there are some precedence relations between them. furthermore sequence-dependent setup times and anticipatory setups are included in the proposed model. the objective is ...

In this paper, we consider a flow shop scheduling problem with availability constraints (FSSPAC) for the objective of minimizing the makespan. In such a problem, machines are not continuously available for processing jobs due to preventive maintenance activities. We proposed a mixed-integer linear programming (MILP) model for this problem which can generate non-permutation schedules. Furthermor...

A hybrid genetic algorithm (HGA) approach is proposed for a lot-streaming flow shop scheduling problem, in which a job (lot) is split into a number of smaller sublots so that successive operations can be overlapped. The objective is the minimization of the mean weighted absolute deviation of job completion t imes from due dates.

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 programmin...