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...

In this paper, we consider the scheduling problems with exponential learning effect. By the exponential learning effect, we mean that the processing time of a job is defined by an exponent function of the sum of the normal processing times of the already processed jobs. We consider the following objective functions: the makespan, the total completion time, the sum of the quadratic job completio...

One of the most significant optimization issues facing a manufacturing company is flexible flow shop scheduling problem (FFSS). However, FFSS with uncertainty and energy-related elements has received little investigation. Additionally, in order to reduce overall waiting times earliness/tardiness issues, topic shared due dates researched. Using transmission line loadings bus voltage magnitude va...

Even though a very large number of solution methods has been developed for the jobshop scheduling problem, the majority are designed for the makespan criterion. In this paper, we propose a general approach for optimizing any regular criterion in the job-shop scheduling problem. The approach is a local search method that uses a disjunctive graph model and neighborhoods generated by swapping crit...

Original scientific paper This paper presents a hybrid genetic algorithm for assembly flow-shop scheduling problem with sequence-dependent setup and transportation times, with objectives, namely the minimizing of weighted, sum of total weighted squared tardiness, makespan, and total weighted squared earliness and number of tardy jobs. Since the problem is NP-hard, we solved this problem by hybr...