A guided tabu search/path relinking algorithm for the job shop problem

The job shop scheduling problem with makespan criterion is valuable from both practical and theoretical points of view. This problem has been attacked by most of the well-known meta-heuristic algorithms. Among them, tabu search has emerged as the most effective approach. The proposed algorithm takes advantages of both N1 and N6 neighborhoods. N1 neighborhood is used as a path relinking procedure while N6 neighborhood with its guideposts is applied in a tabu search framework. In addition, a method is presented for updating the topological order, heads and tails in N6 neighborhood. The algorithm is tested on standard benchmark sets, outperformed all previous approaches (include i-TSAB) and found six new upper bounds among the unsolved problems. Furthermore, we have tried to collect the newest upper bounds for the other problems.     

Simultaneous Prediction of the Density,Viscosity and Electrical Conductivity of Pyridinium-Based Hydrophobic Ionic Liquids Using Artificial Neural Network

Silicon - An Artificial Neural Network (ANN) model is presented for the Simultaneous prediction of density, viscosity and electrical conductivity of pyridinium-based hydrophobic ionic liquids. Data...     

Improving hydrogen production via water splitting over Pt/TiO2/activated carbon nanocomposite

Mesoporous TiO₂/AC, Pt/TiO₂ and Pt/TiO₂/AC (AC = activated carbon) nanocomposites were synthesized by functionalizing the activated carbon using acid treatment and sol–gel method. Photochemical deposition method was used for Pt loading. The nano-photocatalysts were characterized using XRD, SEM, DRS, BET, FTIR, XPS, CHN and ICP methods. The hydrogen production, under UV light irradiation in an aqueous suspension containing methanol has been studied. The effect of Pt, methanol and activated carbon were investigated. The results show that the activated carbon and Pt together improve the hydrogen production via water splitting. Also methanol acts as a good hole scavenger. Mesoporous Pt/TiO₂/AC nanocomposite is the most efficient photocatalyst for hydrogen production compared to TiO₂/AC, Pt/TiO₂ and the commercial photocatalyst P25 under the same photoreaction conditions. Using Pt/TiO₂/AC, the rate of hydrogen production is 7490 μmol (h g catal.)⁻¹ that is about 75 times higher than that of the P25 photocatalyst.     

Reverse logistics network design using simulated annealing

Reverse logistics is becoming more important in overall industry area because of the environmental and business factors. Planning and implementing a suitable reverse logistics network could bring more profit, customer satisfaction, and a nice social picture for companies. But, most of logistics networks are not equipped to handle the return products in reverse channels. This paper proposes a mixed integer linear programming model to minimize the transportation and fixed opening costs in a multistage reverse logistics network. Since such network design problems belong to the class of NP-hard problems, we apply a simulated annealing (SA) algorithm with special neighborhood search mechanisms to find the near optimal solution. We also compare the associated numerical results through exact solutions in a set of problems to present the high-quality performance of the applied SA algorithm.     

A hybrid scatter search for the partial job shop scheduling problem

This paper presents a special case of the general shop called partial job shop problem. The partial job shop is a more realistic generalization of the mixed shop problem. The problem is formulated as a mixed integer programming model. A scatter search algorithm combined with tabu search and path relinking is used to tackle this problem with makespan criterion. The computational experiments are performed on some problem instances. The results are compared with a lower bound and the effectiveness of the algorithm is shown.     

A scenario tree approach to multi-period project selection problem using real-option valuation method

This paper investigates the relation between information technology (IT) and the change of business operations. We evaluate the geographical demand of companies for customer service interactions. The structure is a separate selection model in which districts play the role of distinguished products. The approximated demand structure is used to evaluate the results of IT on customer size, place selection, and cost preserving. The results verify the higher cost vulnerability of IT-thorough companies but propose that capability to utilize cost different is highly company-specified and that the influence of geographically restricted externalities is even existent. Because the productivity of many IT phenomenon based on network results in which the edge productivity caused by the acceptance of a technology by a site is higher if the rest of the company accepts this technology too, companies have a motivation to need cooperate funding in technology across the business. We grow a mathematical model to investigate this balance and obtain experimental assumptions that relate IT-funding variety to the assignment of decision rights.     

A branch-and-bound algorithm for single machine scheduling with quadratic earliness and tardiness penalties

This paper considers the problem of scheduling a single machine, in which the objective function is to minimize the weighted quadratic earliness and tardiness penalties and no machine idle time is allowed. We develop a branch and bound algorithm involving the implementation of lower and upper bounding procedures as well as some dominance rules. The lower bound is designed based on a lagrangian relaxation method and the upper bound includes two phases, one for constructing initial schedules and the other for improving them. Computational experiments on a set of randomly generated instances show that one of the proposed heuristics, used as an upper bound, has an average gap less than 1.3% for instances optimally solved. The results indicate that both the lower and upper bounds are very tight and the branch-and-bound algorithm is the first algorithm that is able to optimally solve problems with up to 30 jobs in a reasonable amount of time.     

The determination of some heavy metals in food samples by flame atomic absorption spectrometry after their separation-preconcentration on bis salicyl aldehyde, 1,3 propan diimine (BSPDI) loaded on activated carbon

A sensitive and simple method for the simultaneous preconcentration of Cr3+, Fe3+, Cu2+, Ni2+, Co2+ and Zn2+ in real samples has been reported. The method is based on the adsorption of analytes on bis salicyl aldehyde, 1,3 propan diimine (BSPDI) loaded on activated carbon. The adsorbed metals on modified activated carbon were eluted using 8 mL of 2 mol L(-1) nitric acid in acetone or 10 mL of 4 mol L(-1) HNO3. The influences of the analytical parameters including pH and sample volume were investigated. The effects of matrix ions on the retentions of the analytes were also examined. The recoveries of analytes were generally quantitative. The method has been successfully applied for these metals content evaluation in some food samples.     

A GA/TS algorithm for the stage shop scheduling problem

This paper presents a special case of the general shop called stage shop problem. The stage shop is a more realistic generalization of the mixed shop problem. In the stage shop problem, each job has several stages of operations. In order to solve the stage shop problem with makespan objective function, an existing neighborhood of job shop is used. In this neighborhood, few enhanced conditions are proposed to prevent cycle generation. In addition, a new neighborhood for operations that belong to the same job is presented. These neighborhoods are applied to the stage shop problem in a tabu search framework. A genetic algorithm is used to obtain good initial solutions. An existing lower bound of the job shop is adapted to our problem and the computational results have been compared to it. Our algorithm has reached the optimal solutions for more than half of the problem instances.