Abstract: The proper number and appropriate locations of service centers can save cost, raise revenue and gain more satisfaction from customers. Establishing service centers is high-cost and difficult to relocate. In long-term planning periods, several factors may affect the service. One of the most critical factors is uncertain demand of customers. The opened service centers need to be capable of serving customers and making a profit although the demand in each period is changed. In this work, the capacitated location-allocation problem with stochastic demand is considered. A mathematical model is formulated to determine suitable locations of service centers and their allocation to maximize total profit for multiple planning periods. Two heuristic methods, a local search and genetic algorithm, are used to solve this problem. For the local search, five different chances to choose each type of moves are applied. For the genetic algorithm, three different replacement strategies are considered. The results of applying each method to solve numerical examples are compared. Both methods reach to the same best found solution in most examples but the genetic algorithm provides better solutions in some cases.
Abstract: In this paper, the joint optimization of the
economic manufacturing quantity (EMQ), safety stock level,
and condition-based maintenance (CBM) is presented for a partially
observable, deteriorating system subject to random failure. The
demand is stochastic and it is described by a Poisson process.
The stochastic model is developed and the optimization problem
is formulated in the semi-Markov decision process framework. A
modification of the policy iteration algorithm is developed to find
the optimal policy. A numerical example is presented to compare
the optimal policy with the policy considering zero safety stock.
Abstract: This paper is concerned with the single-item
continuous review inventory system in which demand is stochastic
and discrete. The budget consumed for purchasing the ordered items
is not restricted but it incurs extra cost when exceeding specific
value. The unit purchasing price depends on the quantity ordered
under the all-units discounts cost structure. In many actual systems,
the budget as a resource which is occupied by the purchased items is
limited and the system is able to confront the resource shortage by
charging more costs. Thus, considering the resource shortage costs as
a part of system costs, especially when the amount of resource
occupied by the purchased item is influenced by quantity discounts,
is well motivated by practical concerns. In this paper, an optimization
problem is formulated for finding the optimal (r, Q) policy, when the
system is influenced by the budget limitation and a discount pricing
simultaneously. Properties of the cost function are investigated and
then an algorithm based on a one-dimensional search procedure is
proposed for finding an optimal (r, Q) policy which minimizes the
expected system costs.
Abstract: Most papers model Joint Replenishment Problem
(JRP) as a (kT,S) where kT is a multiple value for a common review
period T,and S is a predefined order up to level. In general the (T,S)
policy is characterized by a long out of control period which requires
a large amount of safety stock compared to the (R,Q) policy. In this
paper a probabilistic model is built where an item, call it item(i),
with the shortest order time between interval (T)is modeled under
(R,Q) policy and its inventory is continuously reviewed, while the
rest of items (j) are periodically reviewed at a definite time
corresponding to item
Abstract: This paper proposes a bi-objective model for the
facility location problem under a congestion system. The idea of the
model is motivated by applications of locating servers in bank
automated teller machines (ATMS), communication networks, and so
on. This model can be specifically considered for situations in which
fixed service facilities are congested by stochastic demand within
queueing framework. We formulate this model with two perspectives
simultaneously: (i) customers and (ii) service provider. The
objectives of the model are to minimize (i) the total expected
travelling and waiting time and (ii) the average facility idle-time.
This model represents a mixed-integer nonlinear programming
problem which belongs to the class of NP-hard problems. In addition,
to solve the model, two metaheuristic algorithms including nondominated
sorting genetic algorithms (NSGA-II) and non-dominated
ranking genetic algorithms (NRGA) are proposed. Besides, to
evaluate the performance of the two algorithms some numerical
examples are produced and analyzed with some metrics to determine
which algorithm works better.
Abstract: In this article, the design of a Supply Chain Network
(SCN) consisting of several suppliers, production plants, distribution
centers and retailers, is considered. Demands of retailers are
considered stochastic parameters, so we generate amounts of data via
simulation to extract a few demand scenarios. Then a mixed integer
two-stage programming model is developed to optimize
simultaneously two objectives: (1) minimization the fixed and
variable cost, (2) maximization the service level. A weighting method
is utilized to solve this two objective problem and a numerical
example is made to show the performance of the model.
Abstract: We consider a single-echelon, single-item inventory
system where both demand and lead-time are stochastic. Continuous
review policy is used to control the inventory system. The objective
is to calculate the reorder point level under stochastic parameters. A
case study is presented in Neonatal Intensive Care Unit.
Abstract: This paper deals with a periodic-review substitutable
inventory system for a finite and an infinite number of periods. Here
an upward substitution structure, a substitution of a more costly item
by a less costly one, is assumed, with two products. At the beginning
of each period, a stochastic demand comes for the first item only,
which is quality-wise better and hence costlier. Whenever an arriving
demand finds zero inventory of this product, a fraction of unsatisfied
customers goes for its substitutable second item. An optimal ordering
policy has been derived for each period. The results are illustrated
with numerical examples. A sensitivity analysis has been done to
examine how sensitive the optimal solution and the maximum profit
are to the values of the discount factor, when there is a large number
of periods.
Abstract: Coordinated supply chain represents major challenges
for the different actors involved in it, because each agent responds to
individual interests. The paper presents a framework with the
reviewed literature regarding the system's decision structure and
nature of demand. Later, it characterizes an agri food supply chain in
the Central Region of Colombia, it responds to a decentralized
distribution system and a stochastic demand. Finally, the paper
recommends coordinating the chain based on shared information, and
mechanisms for each agent, as VMI (vendor-managed inventory)
strategy for farmer-buyer relationship, information system for
farmers and contracts for transportation service providers.