Asia-Pacific Journal of Operational Research

This paper deals with the probabilistic multi-vehicle pickup and delivery problem. We develop an efficient neighborhood evaluation procedure which allows to reduce the computational complexity by two orders of magnitude with respect to a straightforward approach. The numerical experiments indicate that, if incorporated in a local search strategy, our neighborhood evaluation technique, provides very good results in terms of computation time reduction and equity of the workload distribution among the available vehicles.

A limestone quarry is the major source for supplying raw materials for cement manufacturing operations. Depending upon the available reserves, a quarry is divided into thousands of mineable blocks. Hence, raw materials inventory is identified in terms of a block model projecting the quantity and quality of critical chemical constituents desired in the cement manufacturing process. An individual block never satisfies the process quality constraints; therefore, the blending of various quarry blocks with few additives purchased from the market becomes a prerequisite. As each block is represented as an integer (0-1) variable, the objective of an optimal quarry production scheduling model is sequential mining of these blocks such that the plant quantity and quality requirements are satisfied at the lowest possible cost. This paper presents a new mixed-integer linear programming (MILP) based blending optimization model accomplishing the defined objective as a short-range production planning tool. The benefits of the model are established through a case study of an existing cement manufacturing operation in the northern part of Pakistan, ensuring significant cost savings compared to schedules produced manually.

Mean value analysis is an elegant tool for determining mean performance measures in queueing models. In this paper we show how mean value analysis can be applied to retrial queues. First, we illustrate the technique for the standard M/G/1 retrial queue with exponential retrial times. After that we show how the relations can be adapted to obtain mean performance measures in more advanced M/G/1-type retrial queues.

We propose a Population based dual-sequence Non-Penalty Annealing algorithm (PNPA) for solving the general nonlinear constrained optimization problem. The PNPA maintains a population of solutions that are intermixed by crossover to supply a new starting solution for simulated annealing throughout the search. Every time the search gets stuck at a local optimum, this crossover procedure is triggered and simulated annealing search re-starts from a new subspace. In both the crossover and simulated annealing procedures, the objective function value and the total solution infeasibility degrees are treated as separate performance criteria. Feasible solutions are assessed according to their objective function values and infeasible solutions are assessed with regard to their absolute degree of constraint infeasibility. In other words, in the proposed approach, there exist two sequences of solutions: the feasible sequence and the infeasible sequence. We compare the population based dual sequence PNPA with the standard single sequence Penalty Annealing (the PA), and with the random seed dual sequence Non-Penalty Annealing (NPA). Numerical experiments show that PNPA is more effective than its counterparts.

This paper reconciles diverse efficiency measures to characterize the operating performance of the National Innovation System (NIS) in 33 Asian and European countries. NIS efficiency rating should be considered as a key element for achieving greater innovation and competitive advantages. This study applies the data envelopment analysis (DEA) approach with the traditional DEA models, bilateral models, and critical performance measures, respectively, combing multiple outputs and inputs to measure the magnitude of performance difference between the countries. Empirical results indicate that the overall technical inefficiencies of the NIS activities in these countries are primarily due to the pure technical inefficiencies rather than the scale inefficiencies. Korea and Taiwan perform very well on their NISs and rank numbers 1 and 2 respectively on the Asian list, while Romania ranks number 1 among the European countries. In addition, the Asian countries are generally better performers than the European countries in production activities. Finally, the key input/output influencing the countries' NIS performance have been identified. The innovative features of Korea, Taiwan and Romania are also discussed.

In this paper, an inventory model for deteriorating items with ramp-type time and price dependent consumption rate over a finite planning horizon is considered. In contrast to the traditional deterministic inventory model with static price over the entire planning horizon or fixed number of price changes over the finite time horizon, an alternative model is derived in which prices and the number of price change are to be decision variables. We show that the total profit function is concave. With the concavity, a solution procedure is presented to determine optimal prices, optimal number of pricing cycles and optimal lot size and optimal profit. We illustrate the model with numerical examples. Sensitivity analysis of the model is also carried out.

In this paper, we investigate a manpower planning problem with single employee type over a long planning horizon. The dynamic demand for manpower must be fulfilled by allocating enough number of employees and each employee has a minimal employment period. A cost objective is concerned where the costs for every employee include salary, recruitment and dismissal costs, in particular, setup cost when recruitment activity occurs in one period. In this paper we first formulate the problem as a dynamic programming model. Then we derive properties of the problem and propose an algorithm to minimize the total manpower-related cost over the entire planning horizon. Next we discuss the influence on the optimal states of changing some parameters and provide the sensitivity analysis of the optimal states concerning the future demands. Finally, we report computational results to illustrate the correctness of the approach and to analyze the influence on the optimal states of changing parameters or changing future demands.