Nobuto Nakamura

A two-stage model for the design of supply chain networks

Abstract This research aims to develop an analytical model of the supplier selection process in designing a supply chain network. The constraints on the capacity of each potential supplier are considered in the process. The assumed objective of the supply chain is to minimize the level of customer dissatisfaction, which is evaluated by two performance criteria: (i) price and (ii) delivery lead time. The overall model operates at two levels of decision-making: the operational level and the chain level. The operational level concerns decisions related to optimizing the manufacturing and logistical activities of each potential supplier in order to meet the customers requirements. At the chain level, all the bids from potential suppliers are evaluated and the final configuration of the supply chain is determined. The structure of the chain depends on the product specifications and on the customers order size. An optimal solution in terms of the models for the two levels can be obtained by using a mixed-integer programming technique.

Model for negotiating the price and due date for a single order with multiple suppliers in a make-to-order environment

The nature of the business of a make-to-order company complicates its procurement activities. This paper is concerned with the development of a model for price and due-date negotiations between a manufacturer and its multiple suppliers in fulfilling a single order from a customer in a make-to-order environment. The developed negotiation model incorporates several established negotiation theories: aspiration level, limit level, natural forces acting on a negotiator and effective alternatives. Instead of presenting a single alternative for an offer in the current round of negotiation, we apply the Interactive Weighted-Tchebycheff method to generate a set of effective alternatives for presentation to the decision-maker in each round of the negotiation process. By giving a set of alternatives, we provide a degree of freedom to incorporate the decision-makers preference in making offers and counter-offers during the negotiation process.

Simulated annealing approach for minimizing the makespan of the general job-shop

A simulated annealing approach is proposed to minimize the makespan of job-shop scheduling. The fundamental idea of this approach is based on the rescheduling activity of the human scheduler. By viewing a Gantt chart of a non-optimal schedule, the human scheduler often finds a better schedule by changing its operation sequence. On the basis of this fact we describe the rescheduling procedure of the human scheduler as a deterministic algorithm, and adopt the simulated annealing method to avoid local minimum states. Computational results show the effectiveness of the proposed approach.

Neural network approach for minimizing the makespan of the general job-shop

Abstract A neural network approach is proposed to minimize the makespan of the job-shop scheduling, which is a combinatorial optimization problem. Our approach is based on the Hopfield interconnected neural networks model. In contrast to the traditional neural network approach based on the Hopfield model, our model changes the threshold values at each transition of neurons in order to make a non-delay schedule in addition to incorporating job- and shop-related constraints. As the modification may lead to non-optimal solutions, we increase the temperature of the network according to the Boltzmann machine mechanism and obtain other schedules until no better solution can be obtained within the specified number of tests. From the numerical experiments, 10 out of 15 problems are solved optimally, and remaining five problems are solved near-optimally within a reasonable computing time.

Decentralized reactive Kanban system

Abstract For multi-stage production and transportation system with unstable changes in product demand, this paper proposes a decentralized reactive Kanban system. In the proposed system, the time series data of the demand from the succeeding stage are monitored at each stage individually, and unstable changes in the demand are detected by utilizing control charts. For the detected unstable changes, the buffer size for each stage is controlled as a reaction to the changes. In order to develop the control rule of the buffer size in the proposed system, the multi-stage production and transportation system considered is decomposed into single-stage processing systems, and the performance of the decomposed system is investigated by the simulation experiments under various stable-demand conditions. Based on the results, a decentralized reactive Kanban system is proposed. The performance of the proposed system is investigated by simulation experiments under various unstable product demand conditions, and the results show the effectiveness of the proposed system.

Group production scheduling for minimum total tardiness Part(I)

Abstract This paper considers the problem of group scheduling on a single stage to minimize total tardiness. It is assumed that jobs are classified into several groups on the basis of group technology. Optimal decision as to scheduling sequences will be made as to product group and specific job. This paper proves basic theorems that establish the relative order in which pairs of groups are processed in an optimal schedule. In general, scheduling problems of moderate size may be at least partially ordered so that very few schedules remain to be searched. Two practical algorithms for determining the optimal group schedule and the near optimal group schedule are proposed. Numerical examples are presented in detail.

Agile control in JIT ordering systems

As a just‐in‐time (JIT) ordering system for multi‐stage production inventory systems, both the kanban system and its alternative, the concurrent ordering system, have been proposed. For both JIT ordering systems, the reactive JIT ordering systems that adjust the buffer size responding to unstable changes in demand were proposed. In addition to the adjustment of buffer size, switching ordering systems between the kanban system and the concurrent ordering system is proposed in order to realize agile control in JIT ordering systems. In the proposed system, the time series data of demand is monitored, and switching the order release systems and adjusting the buffer size are considered when an unstable change in demand is detected with the exponentially weighted moving average charts. The effectiveness of the proposed system is analyzed using simulation experiments under unstable conditions. From these simulation experiments, it is clear that the proposed system can react to unstable changes in demand and satisfy the required level for the mean waiting time of demand. Also, to attain the required level, the proposed system must possess much less work‐in‐process inventories than the previous systems which adjust only the buffer size and do not switch ordering systems.

Push, pull, or hybrid control in supply chain management

In this paper, a model of a supply chain system is constructed, and a mathematical model of three control mechanisms, push and pull controls, and a hybrid control of both controls, is formulated. For the three control mechanisms, the variance of processing quantities at each process and the variance of inventory levels at each inventory station are analysed as performance measures. The effects of the number of branches in each stage, the lead time of each transportation process, and the autocorrelation of demand, are numerically investigated. In addition, by comparing the totals of the variances for the three control mechanisms, it is identified and presented that the hybrid control is superior to the others.

Comparing reactive Kanban and reactive CONWIP

This paper compares a reactive Kanban system to a reactive CONWIP system under conditions of unstable changes in demand using simulation experiments. After an introduction, a model of the JIT ordering systems, the Kanban and the CONWIP systems, is constructed. In order to obtain the fundamental information for developing a control rule of buffer size, the performance of the two types of the JIT ordering systems is analysed under various stable-demand conditions by simulation experiments. Based on the results, the reactive JIT ordering systems are proposed, and the performance of the proposed systems is investigated. The results showed that both of the proposed systems can react to unstable changes in demand and maintain the mean waiting time of demand at less than the required level. In the reactive Kanban system, the total of the mean work-in-process inventories becomes much less than that in the traditional Kanban system without controlling buffer size. However, in the reactive CONWIP system, the total of the mean work-in-process inventories becomes much more than or nearly equal to that in the traditional CONWIP system without controlling buffer size under the strongly correlated or the weakly correlated processing times, respectively. Based on the results, it can be claimed that, in the proposed systems, the reactive Kanban system is more effective to react to unstable changes in demand than the reactive CONWIP system.

Ordering alternatives in JIT production systems

Based on the difference in the information utilized in releasing orders, the three ordering alternatives in Just-in-Time (JIT) production systems, the pure Kanban system, the wellknown Kanban system, and the concurrent ordering system, can be enumerated. A mathematical model of the ordering system for each alternative is formulated, the structural properties of the models are clarified, and the performances of the models are analysed and compared with each other by simulation experiments. As a result, this paper shows that the pure Kanban system or the concurrent ordering system is an efficient ordering alternative among the alternatives considered in this paper. Furthermore, the advantageous domain of the pure Kanban system and that of the concurrent ordering system is clarified.