Genetic Programming (GP) is an evolutionary computation method that optimizes the rules defining relationship between environmental states and system output. GP effective for dynamic environments in which information repeatedly changes multiple times. On other hand, GP, are evaluved as state changes, so acquired distant past disappear time, re-learning required a environment. This paper propose...

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...

Genetic algorithms are a very popular heuristic which have been successfully applied to many optimization problems within the last 30 years. In this chapter, we give a survey on some genetic algorithms for shop scheduling problems. In a shop scheduling problem, a set of jobs has to be processed on a set of machines such that a specific optimization criterion is satisfied. According to the restr...

In hybrid flow shop scheduling problem (HFS) with unrelated parallel machines, a set of n jobs are processed on k machines. A mixed integer linear programming (MILP) model for the HFS scheduling problems with unrelated parallel machines has been proposed to minimize the maximum completion time (makespan). Since the problem is shown to be NP-complete, it is necessary to use heuristic methods to ...

Scheduling is a combinatorial problem with important impact on both industry and commerce. If it is performed well it yields time and efficiency benefits and hence reduces costs. Genetic Algorithms have been applied to solve several types of scheduling problems; Flow Shop, Resource, Staff and Line Balancing have all been tackled. However Jobshop Scheduling is the most common problem of interest...

this paper presented a mixed integer programming for integrated scheduling and process planning. the presented process plan included some orders with precedence relations similar to multiple traveling salesman problem (mtsp), which was categorized as an np-hard problem. these types of problems are also called advanced planning because of simultaneously determining the appropriate sequence and m...

This paper studies the challenging problem of scheduling packet transmissions for data gathering in wireless sensor networks. The focus of our work is to explore the energy-latency tradeoffs in packet transmission using techniques such as modulation scaling. The data aggregation tree – a multiple-source single-sink communication paradigm – is employed for abstracting the packet flow. We conside...

This study considers outsourcing decisions in a flexible flow shop scheduling problem, in which each job can be processed by either an in-house production line or outsourced. The selected objective function aims to minimize the weighted sum of tardiness costs, in-house production costs, and outsourcing costs with respect to the jobs due date. The purpose of the problem is to select the jobs tha...