The capacitated lot sizing and scheduling problem that involves indetermining the production amounts and release dates for several items over a given planning horizonare given to meet dynamic order demand without incu...The capacitated lot sizing and scheduling problem that involves indetermining the production amounts and release dates for several items over a given planning horizonare given to meet dynamic order demand without incurring backloggings. The problem consideringovertime capacity is studied. The mathematical model is presented, and a genetic algorithm (GA)approach is developed to solve the problem. The initial solutions are generated after usingheuristic method. Capacity balancing procedure is employed to stipulate the feasibility of thesolutions. In addition, a technique based on Tabu search (TS) is inserted into the genetic algorithmdeal with the scheduled overtime and help the convergence of algorithm. Computational simulation isconducted to test the efficiency of the proposed hybrid approach, which turns out to improve boththe solution quality and execution speed.展开更多
In order to study the capacitated lot sizing problem for a supply chain of corporate multi-location factories to minimize the total costs of production, inventory and transportation under the system capacity restricti...In order to study the capacitated lot sizing problem for a supply chain of corporate multi-location factories to minimize the total costs of production, inventory and transportation under the system capacity restriction and product due date, while at the same time considering the menu distributed balance, the mathematical programming models are decomposed and reduced from the 3 levels into 2 levels according to the idea of just-in-time production. In order to overcome the premature convergence of ACA (ant colony algorithms), the idea of mute operation is adopted in genetic algorithms and a PACA (parallel ant colony algorithms) is proposed for supply chain optimization. Finally, an illustrative example is given, and a comparison is made with standard BAB (Branch and Bound) and PACA approach. The result shows that the latter is more effective and promising.展开更多
In this article, we propose novel reformulations for capacitated lot sizing problem. These reformulations are the result of reducing the number of variables (by eliminating the backorder variable) or increasing the nu...In this article, we propose novel reformulations for capacitated lot sizing problem. These reformulations are the result of reducing the number of variables (by eliminating the backorder variable) or increasing the number of constraints (time capacity constraints) in the standard problem formulation. These reformulations are expected to reduce the computational time complexity of the problem. Their computational efficiency is evaluated later in this article through numerical analysis on randomly generated problems.展开更多
It is shown that when backorders, setup times and dynamic demand are included in capacitated lot sizing problem, the resulting classical formulation and one of the transportation formulations of the problem (referred ...It is shown that when backorders, setup times and dynamic demand are included in capacitated lot sizing problem, the resulting classical formulation and one of the transportation formulations of the problem (referred to as CLSP_BS) are equivalent. And it is shown that both the formulations are “weak” formulations (as opposed to “strong” formulation). The other transportation version is a strong formulation of CLSP_BS. Extensive computational studies are presented for medium and large sized problems. In case of medium-sized problems, strong formulation produces better LP bounds, and takes lesser number of branch-and-bound (B&B) nodes and less CPU time to solve the problem optimally. However for large-sized problems strong formulation takes more time to solve the problem optimally, defeating the benefit of strength of bounds. This essentially is because of excessive increase in the number of constraints for the large sized problems. Hybrid formulations are proposed where only few most promising strong constraints are added to the weak formulation. Hybrid formulation emerges as the best performer against the strong and weak formulations. This concept of hybrid formulation can efficiently solve a variety of complex real life large-sized problems.展开更多
Our research focuses on the development of two cooperative approaches for resolution of the multi-item capacitated lot-sizing problems with time windows and setup times (MICLSP-TW-ST). In this paper we combine variabl...Our research focuses on the development of two cooperative approaches for resolution of the multi-item capacitated lot-sizing problems with time windows and setup times (MICLSP-TW-ST). In this paper we combine variable neighborhood search and accurate mixed integer programming (VNS-MIP) to solve MICLSP-TW-ST. It concerns so a particularly important and difficult problem in production planning. This problem is NP-hard in the strong sense. Moreover, it is very difficult to solve with an exact method;it is for that reason we have made use of the approximate methods. We improved the variable neighborhood search (VNS) algorithm, which is efficient for solving hard combinatorial optimization problems. This problem can be viewed as an optimization problem with mixed variables (binary variables and real variables). The new VNS algorithm was tested against 540 benchmark problems. The performance of most of our approaches was satisfactory and performed better than the algorithms already proposed in the literature.展开更多
This paper presents an economic lot-sizing problem with perishable inventory and general economies of scale cost functions. For the case with backlogging allowed, a mathematical model is formulated, and several proper...This paper presents an economic lot-sizing problem with perishable inventory and general economies of scale cost functions. For the case with backlogging allowed, a mathematical model is formulated, and several properties of the optimal solutions are explored. With the help of these optimality properties, a polynomial time approximation algorithm is developed by a new method. The new method adopts a shift technique to obtain a feasible solution of subproblem and takes the optimal solution of the subproblem as an approximation solution of our problem. The worst case performance for the approximation algorithm is proven to be （4√2 ＋ 5）/7. Finally, an instance illustrates that the bound is tight.展开更多
We reduce lot sizing problem with (a) Set Up, Production, Shortage and Inventory Costs to lot sizing problem with (b) Set Up, Production, and Inventory Costs. For lot sizing problem (as in (b)), Pochet and Wolsey [1] ...We reduce lot sizing problem with (a) Set Up, Production, Shortage and Inventory Costs to lot sizing problem with (b) Set Up, Production, and Inventory Costs. For lot sizing problem (as in (b)), Pochet and Wolsey [1] have given already integral polyhedral with polynomial separation where a linear program yield “integer” solutions. Thus problem (b) which we have created can be more easily solved by methods available in literature. Also with the removal of shortage variables is an additional computational advantage.展开更多
基金This project is supported by National Natural Science Foundation of China (No.70071017, No.60074011) the Open-lab of Manufacturing System Engineering, Xi'an Jiaotong University, China.
文摘The capacitated lot sizing and scheduling problem that involves indetermining the production amounts and release dates for several items over a given planning horizonare given to meet dynamic order demand without incurring backloggings. The problem consideringovertime capacity is studied. The mathematical model is presented, and a genetic algorithm (GA)approach is developed to solve the problem. The initial solutions are generated after usingheuristic method. Capacity balancing procedure is employed to stipulate the feasibility of thesolutions. In addition, a technique based on Tabu search (TS) is inserted into the genetic algorithmdeal with the scheduled overtime and help the convergence of algorithm. Computational simulation isconducted to test the efficiency of the proposed hybrid approach, which turns out to improve boththe solution quality and execution speed.
文摘In order to study the capacitated lot sizing problem for a supply chain of corporate multi-location factories to minimize the total costs of production, inventory and transportation under the system capacity restriction and product due date, while at the same time considering the menu distributed balance, the mathematical programming models are decomposed and reduced from the 3 levels into 2 levels according to the idea of just-in-time production. In order to overcome the premature convergence of ACA (ant colony algorithms), the idea of mute operation is adopted in genetic algorithms and a PACA (parallel ant colony algorithms) is proposed for supply chain optimization. Finally, an illustrative example is given, and a comparison is made with standard BAB (Branch and Bound) and PACA approach. The result shows that the latter is more effective and promising.
文摘In this article, we propose novel reformulations for capacitated lot sizing problem. These reformulations are the result of reducing the number of variables (by eliminating the backorder variable) or increasing the number of constraints (time capacity constraints) in the standard problem formulation. These reformulations are expected to reduce the computational time complexity of the problem. Their computational efficiency is evaluated later in this article through numerical analysis on randomly generated problems.
文摘It is shown that when backorders, setup times and dynamic demand are included in capacitated lot sizing problem, the resulting classical formulation and one of the transportation formulations of the problem (referred to as CLSP_BS) are equivalent. And it is shown that both the formulations are “weak” formulations (as opposed to “strong” formulation). The other transportation version is a strong formulation of CLSP_BS. Extensive computational studies are presented for medium and large sized problems. In case of medium-sized problems, strong formulation produces better LP bounds, and takes lesser number of branch-and-bound (B&B) nodes and less CPU time to solve the problem optimally. However for large-sized problems strong formulation takes more time to solve the problem optimally, defeating the benefit of strength of bounds. This essentially is because of excessive increase in the number of constraints for the large sized problems. Hybrid formulations are proposed where only few most promising strong constraints are added to the weak formulation. Hybrid formulation emerges as the best performer against the strong and weak formulations. This concept of hybrid formulation can efficiently solve a variety of complex real life large-sized problems.
文摘Our research focuses on the development of two cooperative approaches for resolution of the multi-item capacitated lot-sizing problems with time windows and setup times (MICLSP-TW-ST). In this paper we combine variable neighborhood search and accurate mixed integer programming (VNS-MIP) to solve MICLSP-TW-ST. It concerns so a particularly important and difficult problem in production planning. This problem is NP-hard in the strong sense. Moreover, it is very difficult to solve with an exact method;it is for that reason we have made use of the approximate methods. We improved the variable neighborhood search (VNS) algorithm, which is efficient for solving hard combinatorial optimization problems. This problem can be viewed as an optimization problem with mixed variables (binary variables and real variables). The new VNS algorithm was tested against 540 benchmark problems. The performance of most of our approaches was satisfactory and performed better than the algorithms already proposed in the literature.
基金supported by National Natural Science Foundation of China (No. 10671108 and 70971076)Found for the Doctoral Program of Higher Education of Ministry of Education of China (No. 20070446001)+1 种基金Innovation Planning Project of Shandong Province (No. SDYY06034)Foundation of Qufu Normal University (No. XJZ200849)
文摘This paper presents an economic lot-sizing problem with perishable inventory and general economies of scale cost functions. For the case with backlogging allowed, a mathematical model is formulated, and several properties of the optimal solutions are explored. With the help of these optimality properties, a polynomial time approximation algorithm is developed by a new method. The new method adopts a shift technique to obtain a feasible solution of subproblem and takes the optimal solution of the subproblem as an approximation solution of our problem. The worst case performance for the approximation algorithm is proven to be （4√2 ＋ 5）/7. Finally, an instance illustrates that the bound is tight.
文摘We reduce lot sizing problem with (a) Set Up, Production, Shortage and Inventory Costs to lot sizing problem with (b) Set Up, Production, and Inventory Costs. For lot sizing problem (as in (b)), Pochet and Wolsey [1] have given already integral polyhedral with polynomial separation where a linear program yield “integer” solutions. Thus problem (b) which we have created can be more easily solved by methods available in literature. Also with the removal of shortage variables is an additional computational advantage.
