Uncertainty plays a significant role in modeling and optimization of real world systems. Among uncertain approaches, fuzziness describes impreciseness while for ambiguity another definition is required. Vagueness is a probabilistic model of uncertainty being helpful to include ambiguity into modeling different processes especially in industrial systems. In this paper, a vague set based on dista...

The first comprehensive survey paper on scheduling problems with separate setup times or costs was conducted by Allahverdi et al. (1999), who reviewed the literature since the mid-1960s. Since the appearance of that survey paper, there has been an increasing interest in scheduling problems with setup times (costs) with an average of more than 40 papers per year being added to the literature. Th...

The distributed blocking flow shop scheduling problem (DBFSP) allows modeling the scheduling process in companies with more than one factory. It configures production systems as flow shop lines where the blocking constraint must be considered. To the best of our knowledge, this variant of the distributed permutation flow shop scheduling problem has not been studied. In this working paper, we sh...

this paper investigates the problem of just-in-time permutation flow shop scheduling with limited buffers and linear job deterioration in an uncertain environment. the fuzzy set theory is applied to describe this situation. a novel mixed-integer nonlinear program is presented to minimize the weighted sum of fuzzy earliness and tardiness penalties. due to the computational complexities, the prop...

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...

In this paper, four algorithms based on some single-pass heuristics are proposed to solve the flexible flow-shop group scheduling problems with more than two machine centers, which have the same number of parallel machines. Single-pass heuristics need less computation time than multiple-pass ones. The single-pass heuristics adopted in the paper includes the PT, the Palmer and the Gupta algorith...

The flexible job shop scheduling problem is a well-known combinatorial optimization problem. This paper proposes an improved shuffled frog-leaping algorithm to solve the flexible job shop scheduling problem. The algorithm possesses an adjustment sequence to design the strategy of local searching and an extremal optimization in information exchange. The computational result shows that the propos...

This paper addresses the application of AI techniques in a practical OR problem , i.e. scheduling. Scheduling is a scientific domain concerning the allocation of tasks to a limited set of resources over time. The goal of scheduling is to maximize (or minimize) different optimization criteria such as the makespan (i.e. the completion time of the last operation in the schedule), the occupation ra...

The present paper is an attempt to develop a new heuristic algorithm, find the optimal sequence to minimize the utilization time of the machines and hence their rental cost for two stage specially structured flow shop scheduling under specified rental policy in which processing times and set up time are associated with their respective probabilities including transportation time. Further jo...

The flexible job shop scheduling problem (FJSP) is one of the most difficult NP-hard combinatorial optimization problems. It is extremely difficult to solve the FJSP with the disturbances of manufacturing environment, which is always regarded as the flexible job shop online scheduling problem. This paper proposes a new method based on Process-Tree to solve this type of scheduling problem. Proce...