In the past, we have demonstrated how fuzzy concepts can easily be used in the Johnson algorithm to manage uncertain scheduling on two-machine flow shops. This paper extends application to fuzzy flow shops with more than two machines. A new fuzzy heuristic flow-shop scheduling algorithm (the fuzzy Palmer algorithm) is then designed since optimal solutions seem unnecessary for uncertain environm...

Scheduling is an important process widely used in manufacturing, production, management, computer science, and so on. Appropriate scheduling can reduce material handling costs and time. Finding good schedules for given sets of jobs can thus help factory supervisors effectively control job flows and provide solutions for job sequencing. In simple flow shop problems, each machine operation center...

In this paper, cellular manufacturing scheduling problems are studied. The objective is to minimize makespan (Cmax) considering part family in the manufacturing cell flow line where the setup times are sequence dependent. Minimizing Cmax will result in the increment of output rate and the speed of manufacturing systems which is the main goal of such systems. This problem is solved using Ant Col...

Flow shop scheduling problem has a wide application in the manufacturing and has attracted much attention in academic fields. From other point, on time delivery of products and services is a major necessity of companies’ todays; early and tardy delivery times will result additional cost such as holding or penalty costs.  In this paper, just-in-time (JIT) flow shop scheduling problem with preemp...

Scheduling problems naturally arise in supply chains, ranging from manufacturing and business levels in a single firm through multi-organizational processes. In these environments, jobs are served by various resources. As scheduling choices are often decentralized, an inferior system solution may occur. In this paper we investigate a decentralized job-shop system, where jobs are processed utili...

This paper proposes an effective multi-objective differential evolution algorithm (MDES) to solve a permutation flow shop scheduling problem (PFSSP) with modified Dejong's learning effect. The proposed algorithm combines the basic differential evolution (DE) with local search and borrows the selection operator from NSGA-II to improve the general performance.  First the problem is encoded with a...

In this paper, we analyze the characteristics of the dynamic job shop scheduling problem when machine breakdown and new job arrivals occur. A hybrid approach involving neural networks(NNs) and geneticalgorithm(GA) is presented to solve the dynamic job shop scheduling problem as a static scheduling problem. The objective of this kind of job shop scheduling problem is minimizing the completion ti...

The resource constraint project scheduling problem (RCPSP) is an NP-hard benchmark problem in scheduling which takes into account the limitation of resources’ availabilities in real life production processes and subsumes open-shop, job-shop, and flow-shop scheduling as special cases. We here present an application of machine learning to adapt simple greedy strategies for the RCPSP. Iterative re...