The problem of distribution centers location with multiple practical constraints, such as soft service time window, rigid work time window, vehicle being reused and so on, is shown firstly. Secondly, a multi-factor in...
详细信息
ISBN:
(纸本)9781612842011
The problem of distribution centers location with multiple practical constraints, such as soft service time window, rigid work time window, vehicle being reused and so on, is shown firstly. Secondly, a multi-factor integrated optimization model is given, which not only optimizes distribution centers location and vehicle routes, but also meets all the multiple practical constraints. A bi-level nested genetic algorithm is proposed thirdly, where the design of the lower algorithm meets various constraints of optimization. Finally, the feasibility of the model and the efficiency of the algorithm are tested by a numerical example.
Multi-species conservation is of critical concern in ecosystem management science. In this context, modeling the effect of strategic threats on decision-making is a challenging problem that has not been sufficiently a...
详细信息
Multi-species conservation is of critical concern in ecosystem management science. In this context, modeling the effect of strategic threats on decision-making is a challenging problem that has not been sufficiently addressed. Using a security game approach, this paper investigates the optimal conservation of a food web against a strategic threat. The model builds upon the non-cooperative Stackelberg game, wherein conservator (defender) and adversary (attacker) play as leader and follower, respectively. The objective of the defender is to preventively maximize the entire web reliability, under financial and ecological constraints. The defender optimally manipulates the populations of an optimal subset of species to achieve this. In contrast, the attacker attempts to maximize web unreliability by decreasing the population of selected species, using limited resources. A metaheuristic algorithm is developed to compute the equilibrium strategy, and the model is validated through numerical examples. Additionally, in a scenario-based approach, it is examined how the defense and attack strategies, as well as food web reliability, change as the population of keystone species change. The results also show that the combinational use of mathematical optimization and food web-specific conservation prioritization indices yields a practical tool for food web conservation prioritization. The results specifically yield theoretical insights into how to optimally control trophic cascade effects due to changing keystone species populations. A step-wise methodology is proposed to implement the model.
Product portfolio management (PPM) is a critical decision-making for companies across various industries in today's competitive environment. Traditional studies on PPM problem have been motivated toward engineerin...
详细信息
Product portfolio management (PPM) is a critical decision-making for companies across various industries in today's competitive environment. Traditional studies on PPM problem have been motivated toward engineering feasibilities and marketing which relatively pay less attention to other competitors' actions and the competitive relations, especially in mathematical optimization domain. The key challenge lies in that how to construct a mathematical optimization model to describe this Stackelberg game-based leader-follower PPM problem and the competitive relations between them. The primary work of this paper is the representation of a decision framework and the optimization model to leverage the PPM problem of leader and follower. A nonlinear, integer bi-level programming model is developed based on the decision framework. Furthermore, a bi-level nested genetic algorithm is put forward to solve this nonlinear bi-level programming model for leader-follower PPM problem. A case study of notebook computer product portfolio optimization is reported. Results and analyses reveal that the leader-follower bi-level optimization model is robust and can empower product portfolio optimization.
The problem of distribution centers location with multiple practical constraints,such as soft service time window,rigid work time window,vehicle being reused and so on,is shown ***,a multi-factor integrated optimizati...
详细信息
The problem of distribution centers location with multiple practical constraints,such as soft service time window,rigid work time window,vehicle being reused and so on,is shown ***,a multi-factor integrated optimization model is given,which not only optimizes distribution centers location and vehicle routes,but also meets all the multiple practical constraints.A bi-level nested genetic algorithm is proposed thirdly,where the design of the lower algorithm meets various constraints of ***,the feasibility of the model and the efficiency of the algorithm are tested by a numerical example.
The problem of distribution centers location with multiple practical constraints, such as soft service time window, rigid work time window, vehicle being reused and so on, is shown firstly. Secondly, a multi-factor in...
详细信息
The problem of distribution centers location with multiple practical constraints, such as soft service time window, rigid work time window, vehicle being reused and so on, is shown firstly. Secondly, a multi-factor integrated optimization model is given, which not only optimizes distribution centers location and vehicle routes, but also meets all the multiple practical constraints. A bi-level nested genetic algorithm is proposed thirdly, where the design of the lower algorithm meets various constraints of optimization. Finally, the feasibility of the model and the efficiency of the algorithm are tested by a numerical example.
暂无评论