This paper considers a scheduling problem of a set of independent jobs on unrelated parallel machines (UPMs) that minimizesthe maximum completion time (i.e., makespan or ), maximum earliness ( ), and maximum tardiness ( ) simultaneously. Jobs have non-identical due dates, sequence-dependent setup times and machine-dependentprocessing times. A multi-objective mixed-integer linear programmi...

The aim of this paper is to propose a new particle swarm optimization algorithm to solve a hybrid flowshop scheduling with sequence-dependent setup times problem, which is of great importance in the industrial context. This algorithm is called diversified particle swarm optimization algorithm which is a generalization of particle swarm optimization algorithm and inspired by an anarchic society ...

This paper considers single machine scheduling and due date assignment with setup time. The setup time is proportional to the length of the already processed jobs; that is, the setup time is past-sequence-dependent (p-s-d). It is assumed that a job's processing time depends on its position in a sequence. The objective functions include total earliness, the weighted number of tardy jobs, and the...

This paper introduces a tabu search heuristic for a production scheduling problem with sequence-dependent and time-dependent setup times on a single machine. The problem consists in scheduling a set of dependent jobs, where the transition between two jobs comprises an unrestricted setup that can be performed at any time, and a restricted setup that must be performed outside of given time interv...

This paper addresses a single-machine problem in which the past-sequence-dependent p-s-d setup times and exponential time-dependent and position-dependent learning effects are considered. By the exponential time-dependent learning effect, it means that the processing time of a job is defined by an exponent function of the total actual processing time of the already processed jobs. The setup tim...

This paper aims to study a real case of an optimization problem derived from hospital supply chain. The present work focuses on developing operational decision support models and algorithms for production process scheduling in catering. addressed system is considered as flexible job shop system. objective minimize the total flow time. A novel mathematical model two metaheuristics multi-product ...

Each of n items (products) is to be processed on two, capacity limited machines in order to satisfy known demands in each of T periods. Only one item can be processed on each machine at any given time and period. Each switch from one item to another requires sequence dependent setup time. The object is to minimize the sum of the costs of production, storage and setup. We define a quadratic mixe...

Lagrangian relaxation technique is successfully applied to solve sequence dependent setup time flowshop problem to minimize the total weighted tardiness. The relaxed problem can be decomposed into each job-level subproblem that can be effectively solved by dynamic programming. Two types of the additional constraints for the violation of sequence dependent setup time constraints are imposed to t...