Partner Selection With Fuzzy Completion Time And Fuzzy Due Date In A Manufacturing Virtual Enterprise

A virtual enterprise is a temporary alliance of autonomous, and possiblygeographically dispersed enterprises that share the core resources or competenciesamong partners. Partner selection is a major issue in the formation of a virtualenterprise, it is directly related to the success of virtual enterprise. With fuzzycompletion time and fuzzy due date, partner selection in a manufacturing virtualenterprise is studied in this dissertation, including partner selection process model,partner selection mathematical model and optimization algorithm, groupdecision-making algorithm, partner selection service platform.On the side of partner selection process model, this dissertation presents afour-phase partner selection model including project identification, projectdecomposition, preliminary selection and combinatorial optimization. Then Petri-netis used to build the dynamic model of partner selection process, and the reachability,boundness and liveness of the dynamic model are analyzed.On the side of partner selection mathematical model and optimization algorithm,this dissertation firstly introduces fuzzy sets theory to describe the completion timeand due date of the candidates, and then defines the concept of customer satisfactiondegree. Finally, dissertation studies partner selection mathematical model andoptimization algorithm in terms of two kinds of situations. When there is only one atmost customer satisfaction degree between correlative task pair equal to zero,dissertation builds the satisfaction degree-based mathematical model, the objectivesof the model are to maximize the minimum customer satisfaction degree, the averagecustomer satisfaction degree and minimize the cost. Then, an adaptive geneticalgorithm is proposed to solve the formulated problem. When there are severalcustomer satisfaction degree between correlative task pair equal to zero, dissertationdefines the concept of satisfiability degree based on intuitionistic fuzzy sets, thenbuilds the intuitionistic fuzzy sets-based mathematical model, the objectives of the model are to maximize the due date satisfiability degree, the average due datesatisfiability degree and the cost satisfiability degree. Finally, an improved chaosparticle swarm optimization algorithm is proposed to solve the formulated problem.On the side of partner selection group decision-making algorithm, this dissertationpresents a three-phase algorithm for satisfaction degree-based mathematical modeland intuitionistic fuzzy sets-based mathematical model, respectively. Phase1,according to different weight given by each expert, single person multi-objectivedecision-making can be carried out for several times in terms of the satisfactiondegree-based mathematical model and intuitionistic fuzzy sets-based mathematicalmodel, respectively. So, we can obtain several combinations of partners. Phase2,multi-person decision-making evaluation matrix is constructed, and then, we can getthe sort matrix of the combination given by each expert. Phase3, the partnercombination is scored by using Borda function. The larger the score is, the better thepartner combination is. Thus, we can achieve the optimal combination of partnersbased on group decision-making.An ASP model-based manufacturing virtual enterprise partner selection serviceplatform is built, and the physical structure and system structure of the platform aredesigned based on J2EE. Furthermore, a prototype system of the platform isdeveloped.