For short-term scheduling of crude oil operations, oil residency time and high fusion crude oil transportation constraints are difficult to model. With high setup cost for high fusion point oil transportation, it is desired that the volume of such oil should be transported as much as possible by a single setup. To do so and obtain a feasible schedule, charging tank cycling is an effective strategy. With a hybrid Petri net model, scheduling analysis is carried out and schedulability conditions under a charging tank cycling strategy are presented. They can be used for determining a refining schedule and checking if a target refining schedule is realizable. If so, a detailed feasible schedule can be easily obtained by creating the operation decisions one by one and put into immediate industrial use.

Agility is the competitive advantage in the global manufacturing environment. It is believed that the agility can be realized by dynamically reconfigurable virtual enterprise. However, the configuration of virtual enterprises is a challenge to us. In selecting the partners for the reconfiguration of virtualenterprise, many factors should be taken into consideration. However, the manufacturing cost and time to market are the most important factors. In this paper, in considering the completion time as a constraint we model the partner selection problem by an integer programming formulation to minimize the manufacturing cost. The formulation is then transformed into a graph-theoretical formulation and a 2-phase algorithm is developed to solve the problem. In the first phase, a polynomial bounded algorithm is proposed to find the earliest completion time, so we obtained a feasible solution. In phase 2, we improve the solution by exchanging the candidate partners in keeping the solution in the feasible region. Although we may not find the optimal solution for the problem by the improvement algorithm, the objective is reduced iteration by iteration. Thus, the algorithm is efficient and can be applicable to practical problems. An illustrative example is presented to show the application of the proposed algorithm.

It is believed that agile manufacturing is the twenty-?rst century manufacturing enterprise strategy and should be realized by agile virtual enterprise (AVE) which is dynamically con?gured for the manufacturing of one or more products. Agile manufacturing creates a signi?cant challenge for the partner selection in con?guring an AVE. This paper presents a brief introduction to the task decomposition for the manufacturing of a product in multisite environment. A bidding process should be carried out for each task so as to get the information necessary for the con?guration of AVE. To minimize the manufacturing cost, an integer programming (IP) formulation is presented for the partner selection problem. The IP formulation is then transformed into a graph-theoretical formulation by taking the advantage of the precedence relationship between the tasks. The graph obtained turns out to be a directed multipartite graph. Based on the graph-theoretical formulation, an ef?cient solution algorithm is proposed for the problem. It is shown that the algorithm is polynomial bounded. Therefore, it is applicable to large practical problems.