Bi-Objective Flexible Job-Shop Scheduling Problem Considering Energy Consumption under Stochastic Processing Times

Bi-Objective Flexible Job-Shop Scheduling Problem Considering Energy Consumption under Stochastic Processing Times

This paper presents a novel method on the optimization of bi-objective Flexible Job-shop Scheduling Problem (FJSP) under stochastic processing times. The robust counterpart model and the Non-dominated Sorting Genetic Algorithm II (NSGA-II) are used to solve the bi-objective FJSP with consideration of the completion time and the total energy consumption under stochastic processing times. The cas...

A bi-objective model for the assembly flow shop scheduling problem with sequence dependent setup times and considering energy consumption

A Flexible Job Shop Scheduling Problem with Controllable Processing Times to Optimize Total Cost of Delay and Processing

In this paper, the flexible job shop scheduling problem with machine flexibility and controllable process times is studied. The main idea is that the processing times of operations may be controlled by consumptions of additional resources. The purpose of this paper to find the best trade-off between processing cost and delay cost in order to minimize the total costs. The proposed model, flexibl...

Flexible job shop scheduling under availability constraints

In this paper, an exact geometric algorithm is presented for solving two-job sequencing and scheduling problems in flexible flow shop and job shop environments while the resources are (un)available in some time periods and processors (un)availability is the same in all work centers. This study seems utterly new and it is applicable to any performance measure based on the completion time. The in...

Single Objective Evolutionary Algorithm for Flexible Job-shop Scheduling Problem

A meta-heuristic approach for solving the flexible job-shop scheduling problem (FJSP) is presented in this study. This problem consists of two sub-problems, the routing problem and the sequencing problem and is among the hardest combinatorial optimization problems. We propose a Evolutionary Algorithm (EA) for the FJSP. Our algorithm uses several different rules for generating the initial popula...