In industries machine maintenance is used in order to avoid untimely machine fails as well as to improve production effectiveness. This research regards a permutation flow shop scheduling problem with aging and learning effects considering maintenance process. In this study, it is assumed that each machine may be subject to at most one maintenance activity during the planning horizon. The objec...

This paper presents a bi-objective MIP model for the flexible flow shop scheduling  problem (FFSP) in which the total weighted tardiness and the energy consumption are minimized simultaneously. In addition to considering unrelated machines at each stage, the set-up times are supposed to be sequence- and machine-dependent, and it is assumed that jobs have different release tim...

Much attention has been paid to evolutionary multi-objective optimization approaches efficiently solve real-world engineering problems with multiple conflicting objectives. However, the loss of selection pressure and non-uniformity in distribution Pareto optimal solutions objective space can impede both dominance-based decomposition-based optimizers when solving many-objective problems. In this...

This paper proposes a multi-objective model for the economic-statistical design of the variable sample size and sampling interval multivariate exponentially weighted moving average control chart by using double warning lines. The Markov chain approach is used to obtain the statistical properties. We extend the Lorenzen and Vance cost function considering multiple assignable causes and multivari...

Abstract: In order to solve the vehicle routing problem with pickup and delivery (VRPPD), this paper proposed an improved quantum genetic algorithm based on different constraint conditions. Firstly, a mathematical model was established aiming at minimizing the dispatching time and the total cost. Secondly, the paper proposes the improved quantum genetic algorithm and non dominated sorting strat...