Customer Enquiry Management: Part of a Hierarchical System to Control Lead Times in Make-to-Order Companies

The authors are currently developing a hierarchical production planning system specifically designed for the ‘make-to-order’ sector of industry. Its aim is to control the delivery and manufacturing lead times of all orders processed by a firm. Two major decision levels are identified - the customer enquiry stage and the order release stage. Input/output control is exercised at both stages. This paper is concerned with the control mechanisms used at the customer enquiry stage. Two important backlogs of work, along with their associated backlog lengths, are identified. The system aims to maintain these backlogs between predetermined minimum and maximum lengths in order to process all orders within an acceptable length of time. It is shown that the two backlogs are linked in a manner that enables them to be controlled simultaneously. Hence, a procedure for dealing with incoming customer orders is presented.     

A Simple Model for Computing the Trade-Offs between Plant Capacity and Operating Strategies

A method is presented for determining the optimal capacity of a production system which encounters a strong seasonal demand for its output. A model is developed for analysing the trade-offs between plant capacity and different production strategies. The production strategies are computed by linear programming for a range of plant capacities and a given demand pattern. The annual capital costs of the plant are calculated as a function of plant capacity and the two costs are added in order to determine the plant capacity corresponding to the least cost.     

Scheduling Production in a Heavily Constrained Plant – Anode Manufacture in an Aluminium Smelter

In this paper a mathematical model of an anode manufacturing plant is developed with the objective of assisting in the planning and scheduling of production for up to a month ahead. A model of the overall smelter already exists and is based on a monthly time frame. The anode plant is a part of this model but is a very heavily constrained area and it is necessary to have a daily planning model that will help to achieve the optimal level of operations as dictated by the overall model of the smelter. The anode area is responsible for the production of carbon blocks (called anodes) which are an integral part of the aluminium smelting process. The plant is also responsible for the delivery of all raw materials within the smelter. The model developed is a daily one replicated for up to a month ahead, interconnected by opening and closing stocks.     

Minimizing waiting times in a route design problem with multiple use of a single vehicle

In this study we introduce a routing problem with multiple use of a single vehicle and service time in demand points (clients) with the aim of minimizing the sum of clients waiting time to receive service. This problem is relevant in the distribution of aid, in disaster stricken communities, in the recollection and/or delivery of perishable goods and personnel transportation, among other situations, where reaching clients to perform service, fast and fair, is a priority. We consider vehicle capacity and travel distance constraints which force multiple use of the vehicle in the planning horizon. This paper presents and compares two mixed integer formulations for this problem, based on a multi–level network.     

Optimizing fleet size and delivery scheduling for multi-temperature food distribution

In light of the demand for high-quality fresh food, transportation requirements for fresh food delivery have been continuously increasing in urban areas. Jointly delivering foods with different temperature-control requirements is an important issue for urban logistic carriers who transport both low temperature-controlled foods and normal merchandise. This study aims to analyze and optimize medium- and short-term operation planning for multi-temperature food transportation. For medium-term planning, this study optimizes fleet size for carriers considering time-dependent multi-temperature food demand. For short-term planning, this study optimizes vehicle loads and departure times from the terminal for each order of multi-temperature food, taking the fleet size decided during medium-term planning into account. The results suggest that carriers determine departure times of multi-temperature food with demand–supply interaction and deliver food of medium temperature ranges with priority because delivering such food yields more profit.     

快递企业“最后一公里”快件收派优化方案研究

本文以快递公司快件收派服务为背景,对区域收派路线规划问题进行研究,结合A快递公司实际运作情况进行案例分析,综合考虑收派混合、动态性、时间窗和容量约束四个最主要的因素,建立数学模型,设计收派流程,通过改进的禁忌搜索算法在短时间内得到优化的路径结果,并在收派活动进行中动态处理新需求及实时更新收派路径,以提高收派效率。基于该企业实际数据的计算结果表明,本文提出的相应流程和算法比实际操作获得更好的解。     

A customer-centric routing problem with multiple trips of a single vehicle

In this study, we introduce a routing problem with multiple uses of a single vehicle and service time in demand points, minimizing the sum of clients’ waiting time to receive service. This problem is relevant in the distribution of aid in disaster-stricken communities, in the recollection and/or delivery of perishable goods and personnel transportation, among other situations, where reaching clients to perform service, fast and fair, is a priority. We consider vehicle capacity and travel distance constraints, forcing multiple use of the vehicle during the planning horizon. This paper presents two mixed integer formulations for this problem, based on a multi-level network, as well as a metaheuristic algorithm. The proposed models can solve to optimality instances with up to 30 clients. The proposed metaheuristic algorithm obtains high-quality solutions in short computational times.     

Capacitated plant selection in a decentralized manufacturing environment: A bilevel optimization approach

Most facility selection and production planning approaches assume centralized decision making using monolithic models. In this paper, we address a capacitated plant selection problem in a decentralized manufacturing environment where the principal firm and the auxiliary plants operate independently in an organizational hierarchy. A non-monolithic model is developed for plant selection in the decentralized decision making process. The developed model considers the independence relationship between the principal firm and the selected plants. It also takes into account the opportunity costs of over-setting production capacities in the opened plants. The developed mathematical programming model is a two-level nonlinear programming model with integer and continuous decision variables. It was transformed into an equivalent single level model, linearized and solved by available optimization software. Computational examples are presented.     

On the safety stock problem for random delivery processes

Inventory models are considered in which the delivery of an order occurs not on one occasion but at random moments of a period in random parts. We give two extensions of the reliability type inventory model of A. Prékopa. In this model a known constant demand rate is assumed and a simple approximate formula is given for the initial stock of the order period which serves as safety stock and ensures a continuous supply during the whole order period on a prescribed probability level. This formula is widely used in practice for safety stock planning in the case when deliveries in random parts occur.We formulate a generalized version of the random delivery process and derive the exact solution of the safety stock which can be applied also for the previous model. In the second model a random demand rate is considered together with a random delivery process. An exact solution method and a simple approximate formula for the safety stock will be discussed. We have experiences in the application of these models both in a steel works and a textile factory in Hungary.     

A heuristic algorithm for a production planning problem in an assembly system

This paper focuses on a production planning problem in an assembly system operating on a make-to-order basis. Due dates are considered as constraints in the problem, that is, tardiness is not allowed. The objective of the problem is to minimise holding costs for final product inventory as well as work-in-process inventory. A non-linear mathematical model is presented and a heuristic algorithm is developed using a solution property and a network model for defining solutions of the problem. A series of computational tests were done to compare the algorithm with a commercial planning/scheduling software and backward finite-loading methods that employ various priority rules. The results showed that the suggested algorithm outperformed the others.     

Notes on the single route lateral transhipment problem

Previous research has analyzed deterministic and stochastic models of lateral transhipments between different retailers in a supply chain. In these models the analysis assumes given fixed transhipment costs and determines under which situations (magnitudes of excess supply and demand at various retailers) the transhipment is profitable. However, in reality, these depend on aspects like the distance between retailers or the transportation mode chosen. In many situations, combining the transhipments may save transportation costs. For instance, one or more vehicle routes may be used to redistribute the inventory of the potential pickup and delivery stations. This can be done in any sequence as long as the vehicle capacity is not violated and there is enough load on the vehicle to satisfy demand. The corresponding problem is an extension of the one-commodity pickup and delivery traveling salesman and the pickup and delivery vehicle routing problem. When ignoring the routing aspect and assuming given fixed costs, transhipment is only profitable if the quantities are higher than a certain threshold. In contrast to that, the selection of visited retailers is dependent on the transportation costs of the tour and therefore the selected retailers are interrelated. Hence the problem also has aspects of a (team) orienteering problem. The main contribution is the discussion of the tour planning aspects for lateral transhipments which may be valuable for in-house planning but also for price negotiations with external contractors. A mixed integer linear program for the single route and single commodity version is presented and an improved LNS framework to heuristically solve the problem is introduced. Furthermore, the effect of very small load capacity on the structure of optimal solutions is discussed.     

Opportunistic supply chain formation from qualified partners for a new market demand

This paper addresses the problem of short-term supply chain design using the idle capacities of qualified partners in order to seize a new market opportunity. The new market opportunity is characterized by a deterministic forecast over a planning horizon. The production–distribution process is assumed to be organized in stages or echelons, and each echelon may have several qualified partners willing to participate. Partners within the echelon may differ in idle production capacity, operational cost, storage cost, etc, and we assume that idle capacity may be different from one period to another period. The objective is to design a supply chain by selecting one partner from each echelon to meet the forecasted demand without backlog and best possible production and logistics costs over the given planning horizon. The overall problem is formulated as a large mixed integer linear programming problem. We develop a decomposition-based solution approach that is capable of overcoming the complexity and dimensionality associated with the problem. Numerical results are presented to support the effectiveness of this approach.     

Performance analysis and design of supply chains: a Petri net approach

In this paper, we investigated a dynamic modelling technique for analysing supply chain networks using generalised stochastic Petri nets (GSPNs). The customer order arrival process is assumed to be Poisson and the service processes at the various facilities of the supply chain are assumed to be exponential. Our model takes into account both the procurement process and delivery logistics that exist between any two members of the supply chain. We compare the performance of two production planning and control policies, the make-to-stock and the assemble-to-order systems in terms of total cost which is the sum of inventory carrying cost and cost incurred due to delayed deliveries. We formulate and solve the decoupling point location problem in supply chains as a total relevant cost (sum of inventory carrying cost and the delay costs) minimisation problem. We use the framework of integrated GSPN-queuing network modelling—with the GSPN at the higher level and a generalised queuing network at the lower level—to solve the decoupling point location problem.     

不确定条件下双目标组批生产的交货期设置研究

交货期是调度方法的函数,因而具有不确定性.研究变批量、变批次、变生产能力下,单阶段、双目标有条件相容组批的交货期设置问题,将它转化为订单投放策略和调度模式研究.建立了一个基于目标的双目标订单投放策略数学模型.采用目标序列优先方法进行双目标求解,用两种调度模式求出区间值,进行最优交货期逼近.模式1:松弛掉产品加工约束条件,基于负荷考虑、给出离散生产模式下订单完工率最大的订单排序算法,算法综合考虑了任务紧急程度、可调度性、重要度和流程时间最短四个方面,得到区间的一个端点.模式2是有条件相容的启发式组批调度算法,即通过聚类计算将订单安排问题转化为多队列调度问题,将新来订单的投放转化为某个队列的插单和批量分割问题,不同队列中批的投产顺序由批中优先级最高的订单决定,并在能力约束下进行批量分割计算,得到区间的另一个端点,结合流程可靠性求出区间.实例证明,模式2的交货期设置小,订单完工率和生产率高.     

An adapted heuristic approach for a clustered traveling salesman problem with loading constraints

The joint optimization of routing and loading operations is crucial to fully optimize the overall planning process in logistics, and as a result routing problems with side constraints are becoming more and more important during the last years. This paper approaches the design of optimal routes for pickup and delivery operations considering in addition some capacity and loading constraints on the vehicles to be used. It is focused on exploiting new ideas to deal with real life situations in which the customers are not uniformly distributed on the pickup or delivery regions of the problem. An adapted and effective heuristic based on a Variable Neighborhood Search framework using improved neighborhood structures is proposed and discussed. The algorithm is applied to several new sets of instances with special structures to better represent real life situations, providing computational results to evaluate its performance.     

Plant location and procurement planning in knockdown production systems

We consider an integrated problem of plant location and capacity planning for components procurement in knockdown production systems. The problem is that of determining the schedule of opening components manufacturing plants, plans for acquisition of capacities in opened components manufacturing plants, and plans for components procurement in final assembly plants with the objective of minimizing the sum of fixed costs for opening plants, acquisition and operation costs of facilities, and delivery and subcontracting costs of components. The problem is formulated as a mixed integer linear program and solved by a two-stage solution procedure. In the solution procedure, the problem is decomposed into two tractable subproblems and these subproblems are solved sequentially. In the first stage, a dynamic plant location problem is solved using a cut and branch algorithm based on Gomory cuts, while a multiperiod capacity planning problem is solved in the second stage by a heuristic algorithm that uses a cut and branch algorithm and a variable reduction scheme. The solution procedure is tested on problems of a practical size and results show that the procedure gives reasonably good solutions.     

Waiting time in a multi-server cutoff-priority gueue, and its application to an urban ambulance service

We consider a priority queue in steady state with N servers, two classes of customers, and a cutoff service discipline. Low priority arrivals are "cut off" (refused immediate service) and placed in a queue whenever N1 or more servers are busy, in order to keep N-N1 servers free for high priority arrivals. A Poisson arrival process for each class, and a common exponential service rate, are assumed. Two models are considered: one where high priority customers queue for service and one where they are lost if all servers are busy at an arrival epoch. Results are obtained for the probability of n servers busy, the expected low priority waiting time, and (in the case where high priority customers do not queue) the complete low priority waiting time distribution. The results are applied to determine the number of ambulances required in an urban fleet which serves both emergency calls and low priority patients transfers.     

Optimal policy for a dynamic,non-stationary,stochastic inventory problem with capacity commitment

This paper studies a single-product, dynamic, non-stationary, stochastic inventory problem with capacity commitment, in which a buyer purchases a fixed capacity from a supplier at the beginning of a planning horizon and the buyer’s total cumulative order quantity over the planning horizon is constrained with the capacity. The objective of the buyer is to choose the capacity at the beginning of the planning horizon and the order quantity in each period to minimize the expected total cost over the planning horizon. We characterize the structure of the minimum sum of the expected ordering, storage and shortage costs in a period and thereafter and the optimal ordering policy for a given capacity. Based on the structure, we identify conditions under which a myopic ordering policy is optimal and derive an equation for the optimal capacity commitment. We then use the optimal capacity and the myopic ordering policy to evaluate the effect of the various parameters on the minimum expected total cost over the planning horizon.     

Managing capacity flexibility in make-to-order production environments

This paper addresses the problem of managing flexible production capacity in a make-to-order (MTO) manufacturing environment. We present a multi-period capacity management model where we distinguish between process flexibility (the ability to produce multiple products on multiple production lines) and operational flexibility (the ability to dynamically change capacity allocations among different product families over time). For operational flexibility, we consider two polices: a fixed allocation policy where the capacity allocations are fixed throughout the planning horizon and a dynamic allocation policy where the capacity allocations change from period to period. The former approach is modeled as a single-stage stochastic program and solved using a cutting-plane method. The latter approach is modeled as a multi-stage stochastic program and a sampling-based decomposition method is presented to identify a feasible policy and assess the quality of that policy. A computational experiment quantifies the benefits of operational flexibility and demonstrates that it is most beneficial when the demand and capacity are well-balanced and the demand variability is high. Additionally, our results reveal that myopic operating policies may lead a firm to adopt more process flexibility and form denser flexibility configuration chains. That is, process flexibility may be over-valued in the literature since it is assumed that a firm will operate optimally after the process flexibility decision. We also show that the value of process flexibility increases with the number of periods in the planning horizon if an optimal operating policy is employed. This result is reversed if a myopic allocation policy is adopted instead.     

Airfreight forwarder shipment planning: A mixed 0–1 model and managerial issues in the integration and consolidation of shipments

The planning and management of air cargo logistics is a complex endeavor, involving collaboration of multiple logistics agents to deliver shipments timely, safely and economically. Airfreight forwarders are third-party brokers/operators who coordinate and manage cargo shipments for their clients. It is important for a forwarder to develop a shipment plan to evaluate the possible integrations and consolidations, to assess whether shipments can meet their respective target delivery dates, and to estimate the amount of costs involved. In this paper, we formulate a forwarder’s shipment planning problem as a mixed 0–1 LP. Effects of integration and consolidation – on the timely delivery of shipments during any phase of the shipping process – are explicitly addressed. A forwarder’s in-house capacity, as well as the available capacity of its partners and sub-contracting agents, are incorporated. We also consider the target cost for a shipment. Based on the special characteristics of the model, we design a customized tabu-search algorithm. We also provide an illustrative case to examine several managerial issues.