Sheltering network planning and management with a case in the Gulf Coast region

This paper studies sheltering network planning and operations for natural disaster preparedness and responses with a two-stage stochastic program. The preparedness phase decides the locations, capacities and resources of new Permanent Shelters. Under each disaster scenario, both evacuees and resources are distributed to shelters in the response phase. To address the computational burden, the L-shaped algorithm is applied to decompose the problem into the scenario level with linear programs. A case study for hurricanes in the Gulf Coast region of the US is conducted to demonstrate the implementation of the proposed model.     

Supply optimization for the production of raw sugar

Based on a case study from Venezuela, the production of raw sugar is investigated. Ideally, sugar mills operate at a constant production rate. However, safety stocks of the raw material cannot be maintained as sugar cane quality deteriorates very rapidly. Sugar cane is therefore continuously sourced in diverse quantities and qualities from hundreds of geographically dispersed haciendas and supplied to the milling process. Furthermore, due to weather conditions changing throughout the year, tight time windows must be observed for harvesting.The approach presented in this paper aims at preserving a constant supply while minimizing the associated costs. The entire planning problem is structured in a hierarchical fashion: (1) cultivation of the haciendas, (2) harvesting, and (3) dispatching of the harvesting crews and equipment. The corresponding optimization models and solution procedures are introduced and applied to the case study problem.     

Budget allocation for permanent and contingent capacity under stochastic demand

We develop a model of budget allocation for permanent and contingent workforce under stochastic demand. The level of permanent capacity is determined at the beginning of the horizon and is kept constant throughout, whereas the number of temporary workers to be hired must be decided in each period. Compared to existing budgeting models, this paper explicitly considers a budget constraint. Under the assumption of a restricted budget, the objective is to minimize capacity shortages. When over-expenditures are allowed, both budget deviations and shortage costs are to be minimized. The capacity shortage cost function is assumed to be either linear or quadratic with the amount of shortage, which corresponds to different market structures or different types of services. We thus examine four variants of the problem that we model and solve either approximately or to optimality when possible. A comprehensive experimental design is designed to analyze the behavior of our models when several levels of demand variability and parameter values are considered. The parameters consist of the initial budget level, the unit cost of temporary workers and the budget deviation penalty/reward rates. Varying these parameters produce several trade-offs between permanent and temporary workforce levels, and between capacity shortages and budget deviations. Numerical results also show that the quadratic cost function leads to smooth and moderate capacity shortages over the time periods, whereas all shortages are either avoided or accepted when the cost function is linear.     

Business processes inter-operation for supply network co-ordination

In a global supply network, the overall improvement of operational efficiency and customer satisfaction can only be achieved through greater co-ordination and collaboration of all the network members. However, full benefits of close co-operation within a global supply network can only be achieved when the business processes of the individual companies can inter-operate. Currently available commercial solutions are inadequate in supporting full network co-ordination in terms of business process changes and technical arrangements. This paper proposes a system that aims to improve the co-ordination of production planning and control activities across the supply network. To achieve this, it is important to develop new business processes and principles for company collaboration and corresponding information systems. This process starts from the identification of business and system requirements, which underlie the general business solutions for network co-ordination, developing the guiding design principles and subsequent process design and system implementation.     

Integrated multi-period cell formation and subcontracting production planning in dynamic cellular manufacturing systems

In this paper, an integrated mathematical model of the multi-period cell formation and production planning in a dynamic cellular manufacturing system (DCMS) is proposed with the aim of minimizing machine, inter/intra-cell movement, reconfiguration, partial subcontracting, and inventory carrying costs. This paper puts emphasis on the effect of the trade-off between production and outsourcing costs on the re-configuration of the cells in cellular manufacturing systems (CMSs) under a dynamic environment, in which the product mix is different from a period to another resulting in the operational dynamism in the cells. The proposed model is verified by a number of numerical examples and related sensitivity analysis.     

Robust optimal policies of production and inventory with uncertain returns and demand

We consider an inventory and production planning problem with uncertain demand and returns, in which the product return process is integrated into the manufacturing process over a finite planning horizon. We first propose an inventory control model for the return and remanufacturing processes with consideration of the uncertainty of the demand and returns. Then a robust optimization approach is applied to deal with the uncertainty of the problem through formulating a robust linear programming model. Moreover, properties on the robust optimization model are studied, and an equivalent robust optimization model based on duality theory is obtained which allows the solutions to be derived more efficiently. Finally, we provide a set of numerical examples to verify the effectiveness of the approach and analyze the effects of the key parameters on the solutions.     

Service-based capacity strategy for manufacturing service duopoly of differentiated prices and lognormal random demand

Globalization of production has ushered in vibrant manufacturing service industries whose business is to serve the production needs of product engineering firms. In these engineering–manufacturing chains, risk of capacity supply is an important concern for product firms as manufacturers are normally conservative in capacity expansion, especially when demand uncertainty and investment risk are high. To provide quality manufacturing services, this risk must be taken into consideration in formulating a capacity strategy. This paper presents a competition analysis method based on supply risk for a manufacturing duopoly of differentiated prices and lognormal random demand. A novel service-based demand rationing rule is first proposed. Reaction curves and equilibrium of capacity strategy are next derived. Finally, competition behavior of the duopoly is analyzed.     

Modeling approaches for the design of resilient supply networks under disruptions

This paper studies various modeling approaches to design resilient supply networks (SN) for the location-transportation problem under uncertainty. The future environment of the SN is shaped by random demands, and by disruptions perturbing depots capacity and ship-to-point demand processes. The paper proposes several stochastic programming models incorporating alternative resilience seeking formulations. A generic approach to model SN disruptions, and to elaborate and evaluate SN designs is also proposed. Experiments are made to compare the SN design models formulated, and recommendations are drawn on the approach to use to design effective and robust supply networks.     

An integrated production planning model for molds and end items

This study develops a mathematical modelling framework for simultaneously generating production plans for molds and the end items that are made with them. The inputs considered are the item demand (assumed constant over an infinite planning horizon), holding costs and shortage costs, together with the molds’ statistical lifetime distribution (in terms of number of uses) and costs pertaining to amortization, preventive replacements and corrective replacements.     

Myopic optimal policy for a multi-period, two-delivery-lead-times, stochastic inventory problem with minimum cumulative commitment and capacity

This paper studies a single-product, multi-period, stochastic inventory problem that imposes the lower and upper bounds on the cumulative order quantity during a planning horizon and allows two delivery lead times. This model includes three features. The first one is that a buyer purchases a fixed capacity from a supplier at the beginning of a planning horizon and the buyer’s total cumulative order quantity during the planning horizon is constrained with the capacity. The second one is that the buyer agrees to purchase the product at least a certain percentage of the purchased capacity during the planning horizon. The third one is that the supplier allows the buyer to order the product with two-delivery-lead-times. We identify conditions under which a myopic ordering policy is optimal. We also develop an algorithm to calculate the optimal capacity when the minimum cumulative order quantity commitment is a certain percentage of the capacity. We then use the algorithm to evaluate the effect of the various parameters on the buyer’s minimum expected total cost during the planning horizon. Our computation shows that the buyer would benefit from the commitments and two-delivery-lead-times.