Ikou Kaku

Development of a fuel consumption optimization model for the capacitated vehicle routing problem

Fuel consumption accounts for a large and increasing part of transportation costs. In this paper, the Fuel Consumption Rate (FCR), a factor considered as a load dependant function, is added to the classical capacitated vehicle routing problem (CVRP) to extend traditional studies on CVRP with the objective of minimizing fuel consumption. We present a mathematical optimization model to formally characterize the FCR considered CVRP (FCVRP) as well as a string based version for calculation. A simulated annealing algorithm with a hybrid exchange rule is developed to solve FCVRP and shows good performance on both the traditional CVRP and the FCVRP in substantial computation experiments. The results of the experiments show that the FCVRP model can reduce fuel consumption by 5% on average compared to the CVRP model. Factors causing the variation in fuel consumption are also identified and discussed in this study.

Deterministic EOQ with partial backordering and correlated demand caused by cross-selling

There has been much work regarding the deterministic EOQ with partial backordering. The majority of these studies assume no correlation in sales, so independent demands across items is applied in the models. However, it is generally recognized that cross-selling effects between items often appear in real contexts. Thus, incorporating such effects in the inventory model in the form of correlated demands makes it of more practical relevance. In this paper, the authors address a two-item inventory system where the demand of a minor item is correlated to that of a major item because of cross-selling. We firstly present a two-item EOQ model with identical order cycles, where the unmet demand of the major item can be partially backordered with lost sales whereas the demand of the minor item must be met without stockouts. This model is further extended to fit a more practical case where the order cycle of the major item is an integer multiple of that of the minor item. The optimal solutions of the two models, as well as the inventory decision procedures, are also developed. Comparative analysis on these two EOQ models has been drawn in the computational study which presents some insights into the parameter effect on the optimal inventory policy.

Solving uncapacitated multilevel lot-sizing problems using a particle swarm optimization with flexible inertial weight

The multilevel lot-sizing (MLLS) problem is a key production planning problem in materials requirements planning (MRP) system. The MLLS problem deals with determining the production lot-sizes of various items appearing in the product structure over a given finite planning horizon to minimize the production cost, the inventory carrying cost, the back ordering cost and etc. This paper proposed a particle swarm optimization (PSO) algorithm for solving the uncapacitated MLLS problem with assembly structure. All the mathematical operators in our algorithm are redefined and the inertial weight parameter can be either a negative real number or a positive one. The feasibility and effectiveness of our algorithm are investigated by comparing the experimental results with those of a genetic algorithm (GA).

Optimization of parts scheduling in multiple cells considering intercell move using scatter search approach

This paper addresses the problem of parts scheduling in a cellular manufacturing system (CMS) by considering exceptional parts processed on machines located in multiple cells. To optimize the scheduling of parts as well as to minimize material handling between cells, the practice has to develop processing sequences for the parts in cells. A commonly chosen objective is to find part sequences within cells which results in a minimum tardiness. This paper proposes a nonlinear mathematical programming model of the problem by minimizing the total weighted tardiness in a CMS. To solve the mathematical model, a scatter search approach is developed, in which the common components of scatter search are redefined and redesigned so as to better fit the problem. This scatter search approach considers two different methods to generate diverse initial solutions and two improvement methods, and adopts the roulette wheel selection in the combination method to further expand the conceptual framework and implementation of the scatter search. The proposed approach is compared with the commercial solver CPLEX on a set of test problems, some of which are large dimensions. Computational results have demonstrated the effectiveness of this scatter search approach.

Modeling and numerical analysis of line-cell conversion problems

In this paper we define a line-cell conversion problem that has been reported as a new technical innovation in Japanese industry, and we construct a mathematical model to describe it. By numerical analysis of the model based on simulation experiments, we gain insight into line-cell conversion problems, such as (1) how many cells should be formatted, (2) how many workers should be assigned in each cell, and (3) how many workers should be rested on a shortened conveyor line when a conveyor assembly line is converted into cells, in order to optimise system performance, which is defined as the total throughput time and total labour power. Therefore, the model can be used as an evaluation tool in the case where (i) a company wants to change its production system (usually a belt conveyor line) to a new one (including cellular manufacturing), and (ii) a company wants to evaluate the performance of its converted system.

Seru: The Organizational Extension of JIT for a Super-Talent Factory

The Toyota production system (TPS) or lean has long been regarded as a powerful approach for managing manufacturing factories. However, in the early 1990s, the TPS was found not to work when it was applied to Japanese electronics companies. TPS is fit for a stable, but not volatile, business environment such as that which the electronics industry belongs. This volatile environment can be described as one with short product life cycles, uncertain product types, and fluctuating production volumes (sometimes mass, sometimes batch, and sometimes very small volumes). Seru, a new production organization, was developed to cope with this environment. Many leading global companies such as Samsung, Sony, Canon, Panasonic, LG, and Fujitsu have adopted seru. Seru overcame a lot of disadvantages inherent in TPS and brought amazing benefits to seru users. For example: 1) Seru requires a much smaller workforce, 2) It can greatly reduce space requirements, and 3) It can reduce lead time, setup time, WIP inventories, finished-product inventories, and cost. This article introduces seru’s history and defines various seru types. A seru pyramid is constructed to compare seru with the TPS. A JIT organization system is introduced. The authors show why applying it can bring great productivity, efficiency, and flexibility to a production organization.

The activity-based aggregate production planning with capacity expansion in manufacturing systems

This paper builds a mixed integer linear programming (MILP) model to mathematically characterize the problem of aggregate production planning (APP) with capacity expansion in a manufacturing system including multiple activity centers. We use the heuristic based on capacity shifting with linear relaxation to solve the model. Two linear relaxations, i.e., a complete linear relaxation (CLR) on all the integer variables and a partial linear relaxation (PLR) on part of the integer variables are investigated and compared in computational experiments. The computational results show that the heuristic based on the capacity shifting with CLR is very fast but yields low-quality solution whereas the capacity shifting with PLR provides high-quality solutions but at the cost of considerable computational time. As a result, we develop a hybrid heuristic combining beam search with capacity shifting, which is capable of producing a high-quality solution within reasonable computational time. The computational experiment on large-scale problems suggests that when solving a practical activity-based APP model with capacity expansion at the industrial level, the capacity shifting with CLR is preferable, and the beam search heuristic could be subsequently utilized as an alternative if the relaxation gap is larger than the acceptable deviation.

Variable neighbourhood simulated annealing algorithm for capacitated vehicle routing problems

This article presents the variable neighbourhood simulated annealing (VNSA) algorithm, a variant of the variable neighbourhood search (VNS) combined with simulated annealing (SA), for efficiently solving capacitated vehicle routing problems (CVRPs). In the new algorithm, the deterministic ‘Move or not’ criterion of the original VNS algorithm regarding the incumbent replacement is replaced by an SA probability, and the neighbourhood shifting of the original VNS (from near to far by k← k+1) is replaced by a neighbourhood shaking procedure following a specified rule. The geographical neighbourhood structure is introduced in constructing the neighbourhood structures for the CVRP of the string model. The proposed algorithm is tested against 39 well-known benchmark CVRP instances of different scales (small/middle, large, very large). The results show that the VNSA algorithm outperforms most existing algorithms in terms of computational effectiveness and efficiency, showing good performance in solving large and very large CVRPs.

A study on human-task-related performances in converting conveyor assembly line to cellular manufacturing

In this paper, we propose a study to analyse the human-task-related performances in converting a Conveyor Assembly Line (CAL) to cellular manufacturing, which include the possible added operational tasks (which is considered a negative factor for the conversion), the skill level and the cross-training of workers. Three theoretical models (CAL, cellular manufacturing and a joint type, CAL+CM) are constructed involving those constraints respectively. A human-factor-based training approach is also represented for the system performance improvement in cellular manufacturing. Assuming the product mix and the skill level of workers are probability variables, simulation experiments based on the data collected from the previous documents are then used to estimate the marginal impact each factor change had on the estimated performance improvement resulting from the conversion. [Received 18 January 2007; Revised 13 July 2007; Accepted 26 July 2007]

How to carry out assembly line–cell conversion? A discussion based on factor analysis of system performance improvements

The line–cell (or line–seru) conversion is an innovation of assembly systems that has received less attention. Its essence is dismantling an assembly conveyor line and adopting a mini-assembly unit, called seru (or cell). In this paper, we discuss how to do such line–cell conversions, especially focusing on assembly cell formation (ACF) and assembly cell loading (ACL). We perform 64 arrays of full factorial experiment analysis that incorporate three factors: work stations, product types, and product lot sizes. We construct a two-objective line–cell conversion model that minimises the total throughput time (TTPT) and the total labour hours (TLH). Three non-dominated solutions obtained from the two-objective model are used to evaluate the performance of the line–cell conversion. By investigating the experimental results of the ACF and the ACL, we summarise several managerial insights that could be used to help successful line–cell conversions.