This paper presents a new mathematical model for the problem of scheduling part families and jobs within each part family in a flow line manufacturing cell where the setup times for each family are sequence dependent and it is desired to minimize the maximum completion time of the last job on the last machine (makespan) while processing parts (jobs) in each family together. Gaining an optimal s...

This paper investigates the development of an effective heuristic to solve the set covering problem (SCP) by applying the meta-heuristic Meta-RaPS (Meta-heuristic for Randomized Priority Search). In Meta-RaPS, a feasible solution is generated by introducing random factors into a construction method. Then the feasible solutions can be improved by an improvement heuristic. In addition to applying...

This paper introduces an interesting meta-heuristic called Meta-RaPS (Meta-heuristic for Randomized Priority Search) for solving combinatorial problems . Meta-RaPS incorporates randomness within priority rules to construct a feasible solution at each iteration. In addition, Meta-RaPS includes improvement heuristics for enhancing the feasible solution already obtained. Applications discussed inc...

in this paper the conditional location problem is discussed. conditional location problems have a wide range of applications in location science. a new meta-heuristic algorithm for solving conditional p-median problems is proposed and results are compared to those of the previous studies. this algorithm produces much better results than the previous formulations.

Today, there are a lot of useful algorithms for covering array (CA) generation, one the branches combinatorial testing. The major CA challenge is generation an with minimum number test cases (efficiency) in appropriate run-time (performance), large systems. strategies classified into several categories: computational and meta-heuristic, to name most important ones. Generally, have high performa...

The most recent approaches of multi-objective optimization constitute application of meta-heuristic algorithms for which, parameter tuning is still a challenge. The present work hybridizes swarm intelligence with fuzzy operators to extend crisp values of the main control parameters into especial fuzzy sets that are constructed based on a number of prescribed facts. Such parameter-less particle ...

A cutting stock problem is one of the main and classical problems in operations research that is modeled as Lp < /div> problem. Because of its NP-hard nature, finding an optimal solution in reasonable time is extremely difficult and at least non-economical. In this paper, two meta-heuristic algorithms, namely simulated annealing (SA) and tabu search (TS), are proposed and deve...

the travelling salesmen problem (tsp) is one of the most important and famous combinational optimization problems that aim to find the shortest tour. in this problem, the salesman starts to move from an arbitrary place called depot and after visiting all nodes, finally comes back to depot. solving this problem seems hard because program statement is simple and leads this problem belonging to np...

wireless sensor networks are the new generation of networks that typically are formed great numbers of nodes and the communications of these nodes are done as wireless. the main goal of these networks is collecting data from neighboring environment of network sensors. since the sensor nodes are battery operated and there is no possibility of charging or replacing the batteries, the lifetime of ...