Abstract This paper explores the characteristics of solutions when scheduling jobs in a shop with parallel machines. Three classical objective functions were considered: makespan, total completion time, and tardiness. These three criteria combined pairs, resulting bi-objective formulations. formulations solved using ε-constraint method to obtain Pareto frontier for each pair. The research is ev...

This paper aims to develop a multi-objective model for scheduling cargo trains faced by the costs of tardiness and earliness, time limitations, queue priority and limited station lines. Based upon the Islamic Republic of Iran Railway Corporation (IRIRC) regulations, passenger trains enjoy priority over other trains for departure. Therefore, the timetable of cargo trains must be determined based...

In this paper, we present a particle swarm optimization for multi-objective job shop scheduling problem. The objective is to simultaneously minimize makespan and total tardiness of jobs. By constructing the corresponding relation between real vector and the chromosome obtained by using priority rule-based representation method, job shop scheduling is converted into a continuous optimization pro...

In this chapter the authors address a hybrid flow shop scheduling problem considering the minimization of the makespan in addition to the sum of earliness and tardiness penalties. This problem is proven to be NP-hard, and consequently the development of heuristic and meta-heuristic approaches to solve it is well justified. So, to deal with this problem, the authors propose a method which consis...

In this paper, we study the multi-machine scheduling problem with earliness and tardiness penalties and sequence dependent setup times. This problem can be decomposedinto two subproblems sequencing and timetabling. Sequencing focuses on assigning each job to a fixed machine and determine the job sequence on each machine. We call such assignment a semi-schedule. Timetabling focuses on finding an...

We present a two-phase model for planning and scheduling of order picking processes. In many warehousing environments order picking processes are organized according to the pick&pack principle. Pickers must build stabile loads during the picking process under strict time constrains. A genetic algorithm with Pareto elitist-based selection has been developed for this multi-criteria optimization p...

Hybrid algorithm based on Particle Swarm Optimization (PSO) and Simulated annealing (SA) is proposed, to solve Flexible Job Shop Scheduling with five objectives to be minimized simultaneously: makespan, maximal machine workload, total workload, machine idle time & total tardiness. Rescheduling strategy used to shuffle workload once the machine breakdown takes place in proposed algorithm. The hy...

Since that a job usually contains several working procedures in actual production, and it’s hard to optimize the flexible collaborative planning, the flexible lot splitting and scheduling of the job simultaneously in batch production mode, a model for multiobjective integration of flexible collaborative planning and fuzzy lot-splitting scheduling is established. We take four performance indicat...

The scheduling process, usually involve the evaluation and selection of one alternative between a set of them. These decisions are not trivial, considering that they usually involve multiple, and sometimes conflicting, criteria. Particularly in scheduling which aim is to find the trade off between loading efficiency and delivery accuracy taking into account holding costs, tardiness penalties an...