Research on the fully fuzzy time-cost trade-off based on genetic algorithms

It is very difficult to estimate exact values of time and cost of an activity in project scheduling process because many uncertain factors, such as weather, productivity level, human factors etc. , dynamically affect them during project implementation process. A GAs-based fully fuzzy optimal time-cost trade-off model is presented based on fuzzy sets and genetic algorithms (GAs). In tihs model all parameters and variables are characteristics by fuzzy numbers. And then GAs is adopted to search for the optimal solution to this model. The method solves the time-cost trade-off problems under an uncertain environment and is proved practicable through a giving example in ship building scheduling.

Delay-area trade-off for MPRM circuits based on hybrid discrete particle swarm optimization

Polarity optimization for mixed polarity Reed-Muller（MPRM） circuits is a combinatorial issue.Based on the study on discrete particle swarm optimization（DPSO） and mixed polarity,the corresponding relation between particle and mixed polarity is established,and the delay-area trade-off of large-scale MPRM circuits is proposed. Firstly,mutation operation and elitist strategy in genetic algorithm are incorporated into DPSO to further develop a hybrid DPSO（HDPSO）.Then the best polarity for delay and area trade-off is searched for large-scale MPRM circuits by combining the HDPSO and a delay estimation model.Finally,the proposed algorithm is testified by MCNC Benchmarks.Experimental results show that HDPSO achieves a better convergence than DPSO in terms of search capability for large-scale MPRM circuits.

Eastern gray squirrels are consistent shoppers of seed traits:insights from discrete choice experiments

Seeds of many hardwood trees are dispersed by scatter-hoarding rodents,and this process is often mediated by the traits of seeds.Although numerous studies have linked seed traits to seed preference by rodents,little is known about how rodents forage for seeds when multiple desirable and undesirable seed traits are available simultaneously.Here,we adopt a novel method of designing choice experiments to study how eastern gray squirrels(Sciurus carolinensis)select for 6 traits(caloric value,protein content,tannin concentration,kernel mass,dormancy period and toughness of shell)among seeds.From n=426 seed-pair presentations,we found that squirrels preferentially consumed seeds with short dormancy or tougher shells,and preferentially cached seeds with larger kernel mass,tougher shells and higher tannin concentrations.By incorporating random effects,we found that squirrels exhibited consistent preferences for seed traits,which is likely due to the fitness consequences associated with maintaining cached resources.Furthermore,we found that squirrels were willing to trade between multiple traits when caching seeds,which likely results in more seed species being cached in the fall.Ultimately,our approach allowed us to compute the relative values of different seed traits to squirrels,despite covariance among studied traits across seed species.In addition,by investigating how squirrels trade among different seed traits,important insights can be gleaned into behavioral mechanisms underlying seed caching(and,thus,seed survival)dynamics as well as evolutionary strategies adopted by plants to attract seed dispersers.We describe how discrete choice experiments can be used to study resource selection in other ecological systems.

A decomposition approach to job-shop scheduling problem with discretely controllable processing times

Job-shop scheduling problem with discretely controllable processing times (JSP-DCPT) is modeled based on the disjunctive graph, and the formulation of JSP-DCPT is presented. A three-step decomposition approach is proposed so that JSP-DCPT can be handled by solving a job-shop scheduling problem (JSP) and a series of discrete time-cost tradeoff problems. To simplify the decomposition approach, the time-cost phase plane is introduced to describe tradeoffs of the discrete time-cost tradeoff problem, and an extreme mode-based set dominant theory is elaborated so that an upper bound is determined to cut discrete time-cost tradeoff problems generated by using the proposed decomposition approach. An extreme mode-based set dominant decomposition algorithm (EMSDDA) is then proposed. Experimental simulations for instance JSPDCPT_FT10, which is designed based on a JSP benchmark FT10, demonstrate the effectiveness of the proposed theory and the decomposition approach.

A New Idea to LP Model for Time-cost Trade-off in Networks

In this paper,a new optimizing model has been designed to the linear programming model for time-cost trade-off in networks by using the characters of network construction. The model cuts down nearly the half number of constraints then enlarges the extent of the application to network optindzation.